Companies today are racing to leverage the latest digital technologies, such as artificial intelligence, blockchain, and cloud computing. However, many companies report that their strategies did not achieve the anticipated business results. This study is the first to apply state of the art NLP models on unstructured data to understand the different clusters of digital strategy patterns that companies are Adopting. We achieve this by analyzing earnings calls from Fortune Global 500 companies between 2015 and 2019. We use Transformer based architecture for text classification which show a better understanding of the conversation context. We then investigate digital strategy patterns by applying clustering analysis. Our findings suggest that Fortune 500 companies use four distinct strategies which are product led, customer experience led, service led, and efficiency led. This work provides an empirical baseline for companies and researchers to enhance our understanding of the field.
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The document proposes a framework called customer process management (CPM) for using customer-related data to create value for customers. CPM was developed through action research projects with industry and government and analysis of case studies. It suggests steps a service provider can take to help customers improve processes and create more value by using data related to their own processes, similar to how business process management uses company data. The framework views individual customer processes as targets that can be measured and improved using relevant customer data, taking a perspective like studies on manufacturing and business processes.
This document presents a framework for securely selecting the best distributor among multiple options in a business-to-business (B2B) e-commerce scenario. It proposes using a decision tree classification model to evaluate distributors based on attributes like forecast of purchase, marketing knowledge, payment history, manufacturer relationships, and advertising support. The framework involves distributors registering for bids, and the manufacturer running the bid process and selection using the decision tree model. The goal is to facilitate an informed and secure decision for choosing a distributor in B2B e-commerce.
A Novel Intelligence-based e-Procurement System to offer Maximum Fairness Ind...IJECEIAES
A perfect auction policy is one of the most strategic elements that contribute to success factor for any e-Procurement system. An auction policy can be only term as an effective if it really offer win-win situation to both the bidder as well as to the merchant. After reviewing existing studies on e-Procurement system, it is found that there isno effective research work focusing on this point and maximum research contribution has limited its scope to certain application or case studis. Hence, the proposed system introduces a novel eProcurement system which is equipped by an itelligence-building process for performing predictive analysis of ongoing auction process. A mathematical modelling is implemented where all teh variables have been formed using practical implementation of auction system and followed by optimization process using regression-based approach. The study outcome shows that proposed system offers better response time and higher predictive accuracy in contrast to existing approaches.
This document discusses a research study on developing a decision tool to help organizations choose the best-fitting technology for their business processes. The study will have three parts:
1. A systematic literature review to understand the historical relationship between business process management and information technology, and to identify new research areas.
2. Developing a Process-Technology Fit theory by extending the Task-Technology Fit theory and testing it through case studies and statistical analysis. This will provide a framework for selecting technologies best suited to organizations' business processes.
3. Building a decision tool or matrix through design science research and validating it. The tool will help practitioners choose technologies aligned with their business processes and organizational context.
The expected outcomes are
Dear students get fully solved assignments
Send your semester & Specialization name to our mail id :
help.mbaassignments@gmail.com
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Effective Marketing Science Applications: Insights from the ISMS-MSI Practice...Felipe Affonso
The document summarizes 25 projects that were finalists for the INFORMS (ISMS Society for Marketing Science) Practice Prize competition from 2003 to 2012. The prize recognizes impactful implementations of marketing science concepts and methods in organizations. The article reviews common factors among the projects, clusters them into groups, develops a framework for successful marketing science model development and application, and discusses insights into how models diffuse and have impact. Key findings include that effective applications span a wide range of problems and techniques, and there are multiple paths to success, including simpler models that provide robust results. Organizational buy-in is critical and can be achieved through various means. Intermediaries often play an important role in introducing and spreading models across organizations.
IRJET- Strength and Workability of High Volume Fly Ash Self-Compacting Concre...IRJET Journal
The document discusses implementing a social customer relationship management (CRM) system for an online grocery shopping platform using customer reviews. It proposes collecting customer reviews from social media and other sources, refining the data, analyzing it using natural language processing and machine learning techniques, and storing the results in a database. This would allow the platform to better understand customer sentiment and needs to improve products, services and the customer experience.
Recent DEA Applications to Industry: A Literature Review From 2010 To 2014inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
The document proposes a framework called customer process management (CPM) for using customer-related data to create value for customers. CPM was developed through action research projects with industry and government and analysis of case studies. It suggests steps a service provider can take to help customers improve processes and create more value by using data related to their own processes, similar to how business process management uses company data. The framework views individual customer processes as targets that can be measured and improved using relevant customer data, taking a perspective like studies on manufacturing and business processes.
This document presents a framework for securely selecting the best distributor among multiple options in a business-to-business (B2B) e-commerce scenario. It proposes using a decision tree classification model to evaluate distributors based on attributes like forecast of purchase, marketing knowledge, payment history, manufacturer relationships, and advertising support. The framework involves distributors registering for bids, and the manufacturer running the bid process and selection using the decision tree model. The goal is to facilitate an informed and secure decision for choosing a distributor in B2B e-commerce.
A Novel Intelligence-based e-Procurement System to offer Maximum Fairness Ind...IJECEIAES
A perfect auction policy is one of the most strategic elements that contribute to success factor for any e-Procurement system. An auction policy can be only term as an effective if it really offer win-win situation to both the bidder as well as to the merchant. After reviewing existing studies on e-Procurement system, it is found that there isno effective research work focusing on this point and maximum research contribution has limited its scope to certain application or case studis. Hence, the proposed system introduces a novel eProcurement system which is equipped by an itelligence-building process for performing predictive analysis of ongoing auction process. A mathematical modelling is implemented where all teh variables have been formed using practical implementation of auction system and followed by optimization process using regression-based approach. The study outcome shows that proposed system offers better response time and higher predictive accuracy in contrast to existing approaches.
This document discusses a research study on developing a decision tool to help organizations choose the best-fitting technology for their business processes. The study will have three parts:
1. A systematic literature review to understand the historical relationship between business process management and information technology, and to identify new research areas.
2. Developing a Process-Technology Fit theory by extending the Task-Technology Fit theory and testing it through case studies and statistical analysis. This will provide a framework for selecting technologies best suited to organizations' business processes.
3. Building a decision tool or matrix through design science research and validating it. The tool will help practitioners choose technologies aligned with their business processes and organizational context.
The expected outcomes are
Dear students get fully solved assignments
Send your semester & Specialization name to our mail id :
help.mbaassignments@gmail.com
or
call us at : 08263069601
Effective Marketing Science Applications: Insights from the ISMS-MSI Practice...Felipe Affonso
The document summarizes 25 projects that were finalists for the INFORMS (ISMS Society for Marketing Science) Practice Prize competition from 2003 to 2012. The prize recognizes impactful implementations of marketing science concepts and methods in organizations. The article reviews common factors among the projects, clusters them into groups, develops a framework for successful marketing science model development and application, and discusses insights into how models diffuse and have impact. Key findings include that effective applications span a wide range of problems and techniques, and there are multiple paths to success, including simpler models that provide robust results. Organizational buy-in is critical and can be achieved through various means. Intermediaries often play an important role in introducing and spreading models across organizations.
IRJET- Strength and Workability of High Volume Fly Ash Self-Compacting Concre...IRJET Journal
The document discusses implementing a social customer relationship management (CRM) system for an online grocery shopping platform using customer reviews. It proposes collecting customer reviews from social media and other sources, refining the data, analyzing it using natural language processing and machine learning techniques, and storing the results in a database. This would allow the platform to better understand customer sentiment and needs to improve products, services and the customer experience.
Recent DEA Applications to Industry: A Literature Review From 2010 To 2014inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
IJERD (www.ijerd.com) International Journal of Engineering Research and Devel...IJERD Editor
This document summarizes a study that aimed to identify value co-creation attributes that influence the UTM Institutional Repository (UTM IR), an e-service application. The study used interviews with UTM IR providers and users to collect data on the e-service based on the DART model of value co-creation. The DART model examines dialogue, access, risk, and transparency between customers and providers. Interview responses were coded according to the DART building blocks. A gap analysis of the coded provider and user responses identified attributes influencing the UTM IR from a value co-creation perspective. The findings aimed to help evaluate the UTM IR e-service based on customer and provider value co-creation.
Selection of Best Alternative in Manufacturing and Service Sector Using Multi...csandit
Modern manufacturing organizations tend to face versatile challenges due to globalization,
modern lifestyle trends and rapid market requirements from both locally and globally placed
competitors. The organizations faces high stress from dual perspective namely enhancement in
science and technology and development of modern strategies. In such an instance,
organizations were in a need of using an effective decision making tool that chooses out optimal
alternative that reduces time, complexity and highly simplified. This paper explores a usage of
new multi criteria decision making tool known as MOORA for selecting the best alternatives by
examining various case study. The study was covered up in two fold manner by comparing
MOORA with other MCDM and MADM approaches to identify its advantage for selecting
optimal alternative, followed by highlighting the scope and gap of using MOORA approach.
Examination on various case study reveals an existence of huge scope in using MOORA for
numerous manufacturing and service applications.
This document describes a fuzzy logic-based decision support system to help business executives select appropriate e-business models. It discusses existing frameworks for classifying e-business models and their limitations. The proposed system uses fuzzy logic to capture executives' linguistic assessments of key business measures. It assesses each business dimension using fuzzy calculations and rules. A prototype was tested with positive feedback from business executives. The system aims to assist decision-making by narrowing the search for suitable e-business models.
The use of genetic algorithm, clustering and feature selection techniques in ...IJMIT JOURNAL
Decision tree modelling, as one of data mining techniques, is used for credit scoring of bank customers.
The main problem is the construction of decision trees that could classify customers optimally. This study
presents a new hybrid mining approach in the design of an effective and appropriate credit scoring model.
It is based on genetic algorithm for credit scoring of bank customers in order to offer credit facilities to
each class of customers. Genetic algorithm can help banks in credit scoring of customers by selecting
appropriate features and building optimum decision trees. The new proposed hybrid classification model is
established based on a combination of clustering, feature selection, decision trees, and genetic algorithm
techniques. We used clustering and feature selection techniques to pre-process the input samples to
construct the decision trees in the credit scoring model. The proposed hybrid model choices and combines
the best decision trees based on the optimality criteria. It constructs the final decision tree for credit
scoring of customers. Using one credit dataset, results confirm that the classification accuracy of the
proposed hybrid classification model is more than almost the entire classification models that have been
compared in this paper. Furthermore, the number of leaves and the size of the constructed decision tree
(i.e. complexity) are less, compared with other decision tree models. In this work, one financial dataset was
chosen for experiments, including Bank Mellat credit dataset.
IRJET- Customer Relationship and Management SystemIRJET Journal
This document discusses a customer relationship management (CRM) system that uses data mining techniques like classification, clustering, and regression to analyze customer data and improve customer relationships. It specifically proposes using fuzzy c-means clustering, which assigns customers to clusters based on membership values rather than binary classifications. This allows a customer to belong to multiple clusters, addressing limitations of traditional k-means clustering. The paper outlines the fuzzy c-means clustering algorithm and concludes it has advantages over crisp clustering methods for segmenting customer data in a CRM system.
SEM Statistical Analyses in Management Strategiesijdms
This paper was to analyse what factors will affect online shoppers’ purchase intention in the e-business environment. This paper discussed a number of conceptual models and following hypotheses. Two typical e-business companies (Alibaba and Amazon) were ideal comparative analysis models. Structural Equation Modelling (SEM) and the factor analysis were adopted for statistical and empirical analyses. The results showed highly positive correlations among the identified factors. The factors indicated a large innovative performance influence. The factors also verified the huge impact in the sustain ability development. These results may provide some vision on how e-business companies can win a competition and increase their
profit
Research Opportunities in India & Keyword Search Over Dynamic Categorized Inf...VNIT-ACM Student Chapter
The document summarizes different types of software companies in India and provides career advice. It discusses services companies that do outsourced work, product development companies that build software products, and research and development companies that conceptualize new products. It recommends gaining experience through internships and networking to find jobs in product development companies, which offer more interesting work than services roles.
This document evaluates the e-business models of three websites - Dell, Paul Kelly, and Mixonic. It analyzes each site based on criteria like revenue sources, costs, market focus, and competitive advantages. Dell is highlighted for its direct sales model and customization options. Paul Kelly's site complements his music business by providing promotional content. Mixonic offers outsourced CD production and distribution services. The document compares the models' strengths in their industries and positions them on a matrix based on market attractiveness and ability to compete.
For more classes visit
www.snaptutorial.com
CIS 336 Final Exam Guide
1)Joe works for a company where the IT department charges him for the number of CRM login accounts
For more course tutorials visit
www.cis336.com
CIS 336 Final Exam Guide
1)Joe works for a company where the IT department charges him for the number of CRM login accounts that are in his department. What type of IT funding model is his company deploying?
2) This project cycle plan chart looks very much like a bar chart and is easy for management to read because of its visual nature.
CIS 336 STR Become Exceptional--cis336str.comclaric132
For more course tutorials visit
www.cis336.com
CIS 336 Final Exam Guide
1)Joe works for a company where the IT department charges him for the number of CRM login accounts that are in his department. What type of IT funding model is his company deploying?
2) This project cycle plan chart looks very much like a bar chart and is easy for management to read because of its visual nature.
The social dynamics of software developmentaliaalistartup
This document summarizes a study examining the software procurement processes between a university and several software vendors over a decade. It presents three case studies of information systems development histories and analyzes them using a social process model to depict how relationships evolved over time. Major events that changed the relationship between parties were identified as "encounters", with stable periods in between labeled "episodes". While traditional models view procurement statically, this longitudinal study revealed the dynamic nature of procurement strategies over time in the case studies.
Using Machine Learning embedded in Organizational Responsibility Model, added to the ten characteristics of the CIO Master and the twelve competencies of the workforce can help lead the Digital Transformation of the traditional public organizations to the Exponential.
For more classes visit
www.snaptutorial.com
CIS 336 Final Exam Guide
1)Joe works for a company where the IT department charges him for the number of CRM login accounts that are in his department. What type of IT funding model is his company deploying?
The document presents a responsibility model that includes accountability, capability, and commitment. The objectives of the model are to help organizations verify their structure and detect policy problems. It also provides a conceptual framework to define corporate, security, and access control policies. The paper reviews previous research and proposes a UML model of responsibility integrating its main concepts and relationships. It also selects a formal system to formally represent the model.
This document describes the development and implementation of a balanced scorecard (BSC) within the Information Services Division (ISD) of a major Canadian financial group consisting of Great-West Life, London Life, and Investors Group. The case company merged the IT divisions of the three companies in 1997 in an effort to reduce costs and achieve synergies. In response to concerns from stakeholders about the value of large IT investments, the CIO formalized performance measurement criteria into a new IT BSC based on prior experiences. The BSC project aims to better align business and IT strategies and demonstrate the value delivered by IT expenditures.
The document discusses cloud computing and strategies for implementing a vision for transforming a business model using cloud computing. It identifies the Australian Government Information Management Office (AGIMO) as an example of a government IT sector. Key performance indicators, organizational principles, human resource principles, and process management principles are discussed as important for achieving strategic goals and objectives to implement the vision.
This document discusses developing an IT value proposition and strategic themes for IT strategy maps. It explores several approaches for constructing the IT value proposition based on case studies of different organizations. Key approaches identified include: 1) linking applications that support business objectives to the strategic IT service portfolio, 2) including business unit strategic outcomes in the IT scorecard using a linkage scorecard, 3) defining IT's role in enabling organizational objectives as the value proposition, and 4) capturing expectations of IT from business units as the value proposition. The document also discusses using information criteria from COBIT to define the customer perspective of an IT strategy map.
This paper illustrates the similarities between the problems of customer churn and employee turnover. An example of employee turnover prediction model leveraging classical machine learning techniques is developed. Model outputs are then discussed to design \& test employee retention policies. This type of retention discussion is, to our knowledge, innovative and constitutes the main value of this paper.
A Networked Perspective On Business Model For Sap Managed ServicesTodd Turner
This document discusses a networked business model perspective for SAP managed services. It begins by reviewing existing business model frameworks and defining key concepts like networked business models. It then discusses SAP managed services and how they require integration of multiple business processes and suppliers. The researcher examines a case study of a company's SAP managed services business model through interviews and documentation to understand the key elements of the networked business model, including the service offered, necessary actors, customers, value exchange, and technology components. The case analysis identifies the specific SAP managed services offered and the actors involved in production, commercialization, and maintenance of the service.
IJERD (www.ijerd.com) International Journal of Engineering Research and Devel...IJERD Editor
This document summarizes a study that aimed to identify value co-creation attributes that influence the UTM Institutional Repository (UTM IR), an e-service application. The study used interviews with UTM IR providers and users to collect data on the e-service based on the DART model of value co-creation. The DART model examines dialogue, access, risk, and transparency between customers and providers. Interview responses were coded according to the DART building blocks. A gap analysis of the coded provider and user responses identified attributes influencing the UTM IR from a value co-creation perspective. The findings aimed to help evaluate the UTM IR e-service based on customer and provider value co-creation.
Selection of Best Alternative in Manufacturing and Service Sector Using Multi...csandit
Modern manufacturing organizations tend to face versatile challenges due to globalization,
modern lifestyle trends and rapid market requirements from both locally and globally placed
competitors. The organizations faces high stress from dual perspective namely enhancement in
science and technology and development of modern strategies. In such an instance,
organizations were in a need of using an effective decision making tool that chooses out optimal
alternative that reduces time, complexity and highly simplified. This paper explores a usage of
new multi criteria decision making tool known as MOORA for selecting the best alternatives by
examining various case study. The study was covered up in two fold manner by comparing
MOORA with other MCDM and MADM approaches to identify its advantage for selecting
optimal alternative, followed by highlighting the scope and gap of using MOORA approach.
Examination on various case study reveals an existence of huge scope in using MOORA for
numerous manufacturing and service applications.
This document describes a fuzzy logic-based decision support system to help business executives select appropriate e-business models. It discusses existing frameworks for classifying e-business models and their limitations. The proposed system uses fuzzy logic to capture executives' linguistic assessments of key business measures. It assesses each business dimension using fuzzy calculations and rules. A prototype was tested with positive feedback from business executives. The system aims to assist decision-making by narrowing the search for suitable e-business models.
The use of genetic algorithm, clustering and feature selection techniques in ...IJMIT JOURNAL
Decision tree modelling, as one of data mining techniques, is used for credit scoring of bank customers.
The main problem is the construction of decision trees that could classify customers optimally. This study
presents a new hybrid mining approach in the design of an effective and appropriate credit scoring model.
It is based on genetic algorithm for credit scoring of bank customers in order to offer credit facilities to
each class of customers. Genetic algorithm can help banks in credit scoring of customers by selecting
appropriate features and building optimum decision trees. The new proposed hybrid classification model is
established based on a combination of clustering, feature selection, decision trees, and genetic algorithm
techniques. We used clustering and feature selection techniques to pre-process the input samples to
construct the decision trees in the credit scoring model. The proposed hybrid model choices and combines
the best decision trees based on the optimality criteria. It constructs the final decision tree for credit
scoring of customers. Using one credit dataset, results confirm that the classification accuracy of the
proposed hybrid classification model is more than almost the entire classification models that have been
compared in this paper. Furthermore, the number of leaves and the size of the constructed decision tree
(i.e. complexity) are less, compared with other decision tree models. In this work, one financial dataset was
chosen for experiments, including Bank Mellat credit dataset.
IRJET- Customer Relationship and Management SystemIRJET Journal
This document discusses a customer relationship management (CRM) system that uses data mining techniques like classification, clustering, and regression to analyze customer data and improve customer relationships. It specifically proposes using fuzzy c-means clustering, which assigns customers to clusters based on membership values rather than binary classifications. This allows a customer to belong to multiple clusters, addressing limitations of traditional k-means clustering. The paper outlines the fuzzy c-means clustering algorithm and concludes it has advantages over crisp clustering methods for segmenting customer data in a CRM system.
SEM Statistical Analyses in Management Strategiesijdms
This paper was to analyse what factors will affect online shoppers’ purchase intention in the e-business environment. This paper discussed a number of conceptual models and following hypotheses. Two typical e-business companies (Alibaba and Amazon) were ideal comparative analysis models. Structural Equation Modelling (SEM) and the factor analysis were adopted for statistical and empirical analyses. The results showed highly positive correlations among the identified factors. The factors indicated a large innovative performance influence. The factors also verified the huge impact in the sustain ability development. These results may provide some vision on how e-business companies can win a competition and increase their
profit
Research Opportunities in India & Keyword Search Over Dynamic Categorized Inf...VNIT-ACM Student Chapter
The document summarizes different types of software companies in India and provides career advice. It discusses services companies that do outsourced work, product development companies that build software products, and research and development companies that conceptualize new products. It recommends gaining experience through internships and networking to find jobs in product development companies, which offer more interesting work than services roles.
This document evaluates the e-business models of three websites - Dell, Paul Kelly, and Mixonic. It analyzes each site based on criteria like revenue sources, costs, market focus, and competitive advantages. Dell is highlighted for its direct sales model and customization options. Paul Kelly's site complements his music business by providing promotional content. Mixonic offers outsourced CD production and distribution services. The document compares the models' strengths in their industries and positions them on a matrix based on market attractiveness and ability to compete.
For more classes visit
www.snaptutorial.com
CIS 336 Final Exam Guide
1)Joe works for a company where the IT department charges him for the number of CRM login accounts
For more course tutorials visit
www.cis336.com
CIS 336 Final Exam Guide
1)Joe works for a company where the IT department charges him for the number of CRM login accounts that are in his department. What type of IT funding model is his company deploying?
2) This project cycle plan chart looks very much like a bar chart and is easy for management to read because of its visual nature.
CIS 336 STR Become Exceptional--cis336str.comclaric132
For more course tutorials visit
www.cis336.com
CIS 336 Final Exam Guide
1)Joe works for a company where the IT department charges him for the number of CRM login accounts that are in his department. What type of IT funding model is his company deploying?
2) This project cycle plan chart looks very much like a bar chart and is easy for management to read because of its visual nature.
The social dynamics of software developmentaliaalistartup
This document summarizes a study examining the software procurement processes between a university and several software vendors over a decade. It presents three case studies of information systems development histories and analyzes them using a social process model to depict how relationships evolved over time. Major events that changed the relationship between parties were identified as "encounters", with stable periods in between labeled "episodes". While traditional models view procurement statically, this longitudinal study revealed the dynamic nature of procurement strategies over time in the case studies.
Using Machine Learning embedded in Organizational Responsibility Model, added to the ten characteristics of the CIO Master and the twelve competencies of the workforce can help lead the Digital Transformation of the traditional public organizations to the Exponential.
For more classes visit
www.snaptutorial.com
CIS 336 Final Exam Guide
1)Joe works for a company where the IT department charges him for the number of CRM login accounts that are in his department. What type of IT funding model is his company deploying?
The document presents a responsibility model that includes accountability, capability, and commitment. The objectives of the model are to help organizations verify their structure and detect policy problems. It also provides a conceptual framework to define corporate, security, and access control policies. The paper reviews previous research and proposes a UML model of responsibility integrating its main concepts and relationships. It also selects a formal system to formally represent the model.
This document describes the development and implementation of a balanced scorecard (BSC) within the Information Services Division (ISD) of a major Canadian financial group consisting of Great-West Life, London Life, and Investors Group. The case company merged the IT divisions of the three companies in 1997 in an effort to reduce costs and achieve synergies. In response to concerns from stakeholders about the value of large IT investments, the CIO formalized performance measurement criteria into a new IT BSC based on prior experiences. The BSC project aims to better align business and IT strategies and demonstrate the value delivered by IT expenditures.
The document discusses cloud computing and strategies for implementing a vision for transforming a business model using cloud computing. It identifies the Australian Government Information Management Office (AGIMO) as an example of a government IT sector. Key performance indicators, organizational principles, human resource principles, and process management principles are discussed as important for achieving strategic goals and objectives to implement the vision.
This document discusses developing an IT value proposition and strategic themes for IT strategy maps. It explores several approaches for constructing the IT value proposition based on case studies of different organizations. Key approaches identified include: 1) linking applications that support business objectives to the strategic IT service portfolio, 2) including business unit strategic outcomes in the IT scorecard using a linkage scorecard, 3) defining IT's role in enabling organizational objectives as the value proposition, and 4) capturing expectations of IT from business units as the value proposition. The document also discusses using information criteria from COBIT to define the customer perspective of an IT strategy map.
This paper illustrates the similarities between the problems of customer churn and employee turnover. An example of employee turnover prediction model leveraging classical machine learning techniques is developed. Model outputs are then discussed to design \& test employee retention policies. This type of retention discussion is, to our knowledge, innovative and constitutes the main value of this paper.
A Networked Perspective On Business Model For Sap Managed ServicesTodd Turner
This document discusses a networked business model perspective for SAP managed services. It begins by reviewing existing business model frameworks and defining key concepts like networked business models. It then discusses SAP managed services and how they require integration of multiple business processes and suppliers. The researcher examines a case study of a company's SAP managed services business model through interviews and documentation to understand the key elements of the networked business model, including the service offered, necessary actors, customers, value exchange, and technology components. The case analysis identifies the specific SAP managed services offered and the actors involved in production, commercialization, and maintenance of the service.
Running head CASE STUDY QUESTIONS 1CASE STUDY QUESTIONS7.docxhealdkathaleen
Running head: CASE STUDY QUESTIONS 1
CASE STUDY QUESTIONS7
Case study questions
Name
Institution
Introduction
The CARE International is known to be a humanitarian organization which offers relief help to regions that are experiencing natural disasters like hurricanes and earthquakes. This paper will focus on answering the case study questions on diverse issues.
1. What were the main challenges encountered by CARE International before they created their warehouse prepositioning model
The challenges faced by CARE international are such as transportation issues, absence of agility, limited aptitude to gather supplies both locally and internationally (Gay, 2015). There is a challenge of the previous means of transportation utilized by vendors which is slow and also very unreliable as well as the cost of relief resources is very high.
2. How does the objective function relate to the organization's need to improve relief services to affected areas?
The objective function need to minimize the time used to respond to natural occurrences as well as transport reliefs to the affected area. The objective function is connected to the need of agency providing shipping relief services to the affected region at minimal response time.
3. Conduct online research and suggest at least three other applications or types of software that could handle the magnitude of variable and constraints CARE International used in their MIP model.
There are three software that can be incorporated to handle constraints Care International utilizes for Mixed-integer programming ideal which are “Mathematical Programming Language (AMPL), Gurobi, and Statistical Analysis System (SAS) (De & Mok, 2016).” These are tools that assist the organization in solving the linear and the quadratic optimization.
4. Elaborate on some benefits CARE International stands to gain from implementing their pre-positioning model on a large scale in future
Warehouse pre-positioning model has some advantages that it offers to CARE International such as they facilitate the delivery relief to the affected region, mostly in the time of the disaster occurrence. This model assist in providing relief in the affected region in relatively short period of time which means that the agency will be in a position to save more lives.
Warehouse pre-positioning model
Figure 1: Warehouse pre-positioning model
Application case
1. Describe the problem that a large company such as HP might face in offering many product lines and options.
One problem they might face is the issue of high cost for introducing new products, designing and manufacturing as well as the issue of supply chain complexity. The institution might face issues such as the unexpected increase in operational expenses, reduction in the forecasting accuracy and increase in the inventory costs.
2. Why is there a possible conflict between marketing and operations?
Yes. Marketing and operation department are the pillars of any organization. How ...
IRJET- Implementing Social CRM System for an Online Grocery Shopping Platform...IRJET Journal
This document presents a proposed system architecture for implementing a social customer relationship management (CRM) system for an online grocery shopping platform using customer reviews and sentiment analysis. The proposed architecture involves collecting customer reviews from social media, preprocessing and analyzing the data using natural language processing techniques like stemming, and storing the results in a database. Sentiment analysis is performed to categorize reviews by aspects and sentiment. The analyzed data is then presented to users through an interface to help the online grocery shopping platform better understand customer needs and improve products/services based on feedback.
The document provides an overview of the technology/software/telecom industry and how Synergetics, a management consulting firm, has helped companies in this sector identify and achieve strategic business objectives through implementation projects. It discusses major changes in the industry such as the growth of cloud computing and subscription models. It then summarizes three implementation projects Synergetics conducted for established IT companies, helping them optimize processes and achieve significant cost savings and revenue increases.
17 Must-Do's to Create a Product-Centric IT OrganizationCognizant
This document discusses transforming an IT organization into a product-centric model. It provides 17 "plays" or steps to take including establishing a CXO steering committee, identifying key business capabilities and mapping them to product lines, strengthening the business-IT partnership, defining new product-centric roles, aligning the IT organizational structure around products rather than projects, starting enablement programs to build a product-centric culture, and establishing communities of practice. The goal is to align the people, processes, and platforms dimensions around a product mindset and ways of working like Agile and DevOps to better deliver customer value and business outcomes.
This document summarizes a case study presentation on how a firm's competitive environment and digital strategic posture influence digital business strategy. It discusses how digital technologies are reshaping traditional business strategies and structures. The summary defines digital business strategy as using digital resources to create value beyond traditional views of IT. It examines how a firm's industry turbulence, concentration, and growth impact its digital investments and outsourcing. The presentation concludes that a firm's digital strategic posture has convergent effects on general IT investment but divergent effects on outsourcing, and that understanding variations in a competitive environment can explain differences in digital strategic posture.
This document is a thesis submitted to Blekinge Institute of Technology that investigates marketing strategies for Software as a Service (SaaS) companies within the logistics vertical niche. It aims to deepen the understanding of how to market vertical SaaS solutions in logistics. The thesis will conduct a multiple case study of 3 SaaS companies to identify their marketing strategies and categorize them using an existing 8-element model. Findings may help validate and update prior models on SaaS marketing strategies, especially for vertical niches like logistics. The research question is: What are the current marketing strategies for SaaS companies within the logistics vertical software niche?
This published paper aggregates and segments the financial projections of client organizations in multiple industries derived by improving master data quality across the enterprise.
Learning Resources Week 2
Frankfort-Nachmias, C., & Leon-Guerrero, A. (2020). Social statistics for a diverse society (9th ed.). Sage Publications.
· Chapter 2, “The Organization and Graphic Presentation Data” (pp. 27-74)
Wagner, III, W. E. (2020). Using IBM® SPSS® statistics for research methods and social science statistics (7th ed.). Thousand Oaks, CA: Sage Publications.
· Chapter 5, “Charts and Graphs”
· Chapter 11, “Editing Output”
Walden University Writing Center. (n.d.). General guidance on data displays. Retrieved from http://waldenwritingcenter.blogspot.com/2013/02/general-guidance-on-data-displays.html
Use this website to guide you as you provide appropriate APA formatting and citations for data displays.
Laureate Education (Producer). (2016j). Visual displays of data [Video file]. Baltimore, MD: Author.
Note: The approximate length of this media piece is 9 minutes.
In this media program, Dr. Matt Jones discusses frequency distributions. Focus on how his explanation might support your analysis in this week’s Assignment. (video attached separately)
sustainability
Case Report
Integrated Understanding of Big Data, Big Data
Analysis, and Business Intelligence: A Case Study
of Logistics
Dong-Hui Jin and Hyun-Jung Kim *
Seoul Business School, aSSIST, 46 Ewhayeodae 2-gil, Seodaemun-gu, Seoul 03767, Korea; [email protected]
* Correspondence: [email protected]; Tel.: +82-70-7012-2722
Received: 5 October 2018; Accepted: 17 October 2018; Published: 19 October 2018
����������
�������
Abstract: Efficient decision making based on business intelligence (BI) is essential to ensure
competitiveness for sustainable growth. The rapid development of information and communication
technology has made collection and analysis of big data essential, resulting in a considerable increase
in academic studies on big data and big data analysis (BDA). However, many of these studies are
not linked to BI, as companies do not understand and utilize the concepts in an integrated way.
Therefore, the purpose of this study is twofold. First, we review the literature on BI, big data,
and BDA to show that they are not separate methods but an integrated decision support system.
Second, we explore how businesses use big data and BDA practically in conjunction with BI through
a case study of sorting and logistics processing of a typical courier enterprise. We focus on the
company’s cost efficiency as regards to data collection, data analysis/simulation, and the results from
actual application. Our findings may enable companies to achieve management efficiency by utilizing
big data through efficient BI without investing in additional infrastructure. It could also give them
indirect experience, thereby reducing trial and error in order to maintain or increase competitiveness.
Keywords: business application; big data; big data analysis; business intelligence; logistics;
courier service
1. Introduction
A growing number of corporations depend on various and cont.
Learning Resources Week 2
Frankfort-Nachmias, C., & Leon-Guerrero, A. (2020). Social statistics for a diverse society (9th ed.). Sage Publications.
· Chapter 2, “The Organization and Graphic Presentation Data” (pp. 27-74)
Wagner, III, W. E. (2020). Using IBM® SPSS® statistics for research methods and social science statistics (7th ed.). Thousand Oaks, CA: Sage Publications.
· Chapter 5, “Charts and Graphs”
· Chapter 11, “Editing Output”
Walden University Writing Center. (n.d.). General guidance on data displays. Retrieved from http://waldenwritingcenter.blogspot.com/2013/02/general-guidance-on-data-displays.html
Use this website to guide you as you provide appropriate APA formatting and citations for data displays.
Laureate Education (Producer). (2016j). Visual displays of data [Video file]. Baltimore, MD: Author.
Note: The approximate length of this media piece is 9 minutes.
In this media program, Dr. Matt Jones discusses frequency distributions. Focus on how his explanation might support your analysis in this week’s Assignment. (video attached separately)
sustainability
Case Report
Integrated Understanding of Big Data, Big Data
Analysis, and Business Intelligence: A Case Study
of Logistics
Dong-Hui Jin and Hyun-Jung Kim *
Seoul Business School, aSSIST, 46 Ewhayeodae 2-gil, Seodaemun-gu, Seoul 03767, Korea; [email protected]
* Correspondence: [email protected]; Tel.: +82-70-7012-2722
Received: 5 October 2018; Accepted: 17 October 2018; Published: 19 October 2018
����������
�������
Abstract: Efficient decision making based on business intelligence (BI) is essential to ensure
competitiveness for sustainable growth. The rapid development of information and communication
technology has made collection and analysis of big data essential, resulting in a considerable increase
in academic studies on big data and big data analysis (BDA). However, many of these studies are
not linked to BI, as companies do not understand and utilize the concepts in an integrated way.
Therefore, the purpose of this study is twofold. First, we review the literature on BI, big data,
and BDA to show that they are not separate methods but an integrated decision support system.
Second, we explore how businesses use big data and BDA practically in conjunction with BI through
a case study of sorting and logistics processing of a typical courier enterprise. We focus on the
company’s cost efficiency as regards to data collection, data analysis/simulation, and the results from
actual application. Our findings may enable companies to achieve management efficiency by utilizing
big data through efficient BI without investing in additional infrastructure. It could also give them
indirect experience, thereby reducing trial and error in order to maintain or increase competitiveness.
Keywords: business application; big data; big data analysis; business intelligence; logistics;
courier service
1. Introduction
A growing number of corporations depend on various and cont.
Business Analysis using Machine LearningIRJET Journal
The document discusses using machine learning techniques like linear regression, random forest, and decision trees to analyze transaction data from a confectionery business in order to forecast product demand and sales. It applies these machine learning algorithms to a dataset containing over 20,000 transactions to analyze factors like product sales over time. The results can help the business optimize product offerings based on demand and improve profitability.
This document proposes developing a competence-based model for securing the internet of things (IoT) in organizations. It aims to define the required set of organizational competences for IoT products and services regarding information security. The research will use a design science methodology to develop and empirically test a model of organizational competence for IoT security based on an existing model. This will help managers assess their competences against future requirements and properly align their IoT approaches regarding customer information security.
Full Paper: Analytics: Key to go from generating big data to deriving busines...Piyush Malik
This document discusses how analytics can help organizations derive business value from big data. It describes how statistical analysis, machine learning, optimization and text mining can extract meaningful insights from social media, online commerce, telecommunications, smart utility meters, and improve security. While tools exist to analyze big data, challenges remain around data security, privacy, and developing skilled talent. The paper aims to illustrate how existing algorithms can generate value from different industry use cases.
STOCK PRICE PREDICTION AND RECOMMENDATION USINGMACHINE LEARNING TECHNIQUES AN...IRJET Journal
This document discusses using machine learning techniques and sentiment analysis of Twitter data to predict stock prices and recommend buying or selling stocks. It evaluates ARIMA, LSTM, and linear regression models for stock price prediction and uses TextBlob to analyze the sentiment of recent tweets about a company and provide recommendations based on the overall sentiment polarity. For Apple stock, ARIMA had the lowest RMSE of 3.54, while LSTM achieved an RMSE of 5.64 after 30 epochs. Sentiment analysis of Apple tweets found an overall positive polarity. The models were also tested on Yes Bank stock.
MBA548-IT Management and InnovationReport 2Managing IS for Bus.docxalfredacavx97
MBA548-IT Management and Innovation
Report 2
Managing IS for Business and Sustainability Value
Fall- 2019
Points: 100
Deadline: Sunday, Dec 11, 2019, 11:59pm. D2L Assignment folder
==========================================
For our class, you will conduct a research project examining IT and IT-enabled innovation management issues surrounding a focal company. We will break this project into two reports. The first report will examine issues relevant to the first half of the class (first six topics), and is due halfway through the semester. The second report will examine issues relevant to the second half of the class (the remaining six topics).
First, you will need to choose a company for your research project. Since you will need access to data on the company’s business operation and performance, it is recommended that you choose a publicly traded company for your study, which will allow you to get access to the companies’ multiple reports, including annual reports, financial statements, Global Reporting Initiatives reports, etc. for your research.
I have the assignment sheets for both reports available on D2L. Please take a look at both assignment sheets to have an idea of what you will need to do for your research project. This will help you in identifying the focal company for your research. Please feel free to contact the professor if you have questions in choosing a company for your project.
==========================================
Report 2 requirements:
For the second report, you will examine the focal company’s IS management strategy. The questions below tie directly to topics 7 to 12.
Task: Use knowledge and materials we have covered this semester to write a report (around 2000 words, not including reference list) to assess a company’s current IT/IS management strategy and recommend a way forward for the company with IT/IS. The targeted audience of your report is the general business audience.
For your research, you could examine the company’s publicly available information (website, last 3 years of annual reports, 10-K reports, Global Reporting Initiative (GRI) reports etc.). You could search these reports using the search terms such as IT, Information Technology, Information Systems, etc.
The report MUST include the following sections, each section will address the questions listed below:
1) Current IT/IS infrastructure and strategic plan (Topic 7): (10 points)
· What is the company’s IT strategic vision? Generally, what is your perception of the company’s view of IS/IT in enabling its business operation and competition? E.g. Does IS/IT play a more supporting role? Or does IS/IT play a more strategic driving role? Does the company see IT as a competitive necessity, or a competitive advantage?
· Examine the companies’ report to find some examples of IT-enabled initiatives. Discuss how they are related to the companies’ overarching IT vision.
2) IT/IS budget, IT-enabled initiatives, and IT Impacts (Topic 8): (15 po.
Similar to Paper Explained: Deep learning framework for measuring the digital strategy of companies from earnings calls (20)
Spine net learning scale permuted backbone for recognition and localizationDevansh16
Convolutional neural networks typically encode an input image into a series of intermediate features with decreasing resolutions. While this structure is suited to classification tasks, it does not perform well for tasks requiring simultaneous recognition and localization (e.g., object detection). The encoder-decoder architectures are proposed to resolve this by applying a decoder network onto a backbone model designed for classification tasks. In this paper, we argue encoder-decoder architecture is ineffective in generating strong multi-scale features because of the scale-decreased backbone. We propose SpineNet, a backbone with scale-permuted intermediate features and cross-scale connections that is learned on an object detection task by Neural Architecture Search. Using similar building blocks, SpineNet models outperform ResNet-FPN models by ~3% AP at various scales while using 10-20% fewer FLOPs. In particular, SpineNet-190 achieves 52.5% AP with a MaskR-CNN detector and achieves 52.1% AP with a RetinaNet detector on COCO for a single model without test-time augmentation, significantly outperforms prior art of detectors. SpineNet can transfer to classification tasks, achieving 5% top-1 accuracy improvement on a challenging iNaturalist fine-grained dataset. Code is at: this https URL.
Sigmoid function machine learning made simpleDevansh16
Another great part of the Machine Learning Made Simple Series.
Actually a family of functions. All functions have a characteristic "S"-shaped curve or sigmoid curve.
The most famous example is the logistic function. Other big ones are tanh and arc tan.
By their nature, they can be used to “squish” input, making them useful in Machine Learning
Accounting for variance in machine learning benchmarksDevansh16
Accounting for Variance in Machine Learning Benchmarks
Xavier Bouthillier, Pierre Delaunay, Mirko Bronzi, Assya Trofimov, Brennan Nichyporuk, Justin Szeto, Naz Sepah, Edward Raff, Kanika Madan, Vikram Voleti, Samira Ebrahimi Kahou, Vincent Michalski, Dmitriy Serdyuk, Tal Arbel, Chris Pal, Gaël Varoquaux, Pascal Vincent
Strong empirical evidence that one machine-learning algorithm A outperforms another one B ideally calls for multiple trials optimizing the learning pipeline over sources of variation such as data sampling, data augmentation, parameter initialization, and hyperparameters choices. This is prohibitively expensive, and corners are cut to reach conclusions. We model the whole benchmarking process, revealing that variance due to data sampling, parameter initialization and hyperparameter choice impact markedly the results. We analyze the predominant comparison methods used today in the light of this variance. We show a counter-intuitive result that adding more sources of variation to an imperfect estimator approaches better the ideal estimator at a 51 times reduction in compute cost. Building on these results, we study the error rate of detecting improvements, on five different deep-learning tasks/architectures. This study leads us to propose recommendations for performance comparisons.
When deep learners change their mind learning dynamics for active learningDevansh16
Abstract:
Active learning aims to select samples to be annotated that yield the largest performance improvement for the learning algorithm. Many methods approach this problem by measuring the informativeness of samples and do this based on the certainty of the network predictions for samples. However, it is well-known that neural networks are overly confident about their prediction and are therefore an untrustworthy source to assess sample informativeness. In this paper, we propose a new informativeness-based active learning method. Our measure is derived from the learning dynamics of a neural network. More precisely we track the label assignment of the unlabeled data pool during the training of the algorithm. We capture the learning dynamics with a metric called label-dispersion, which is low when the network consistently assigns the same label to the sample during the training of the network and high when the assigned label changes frequently. We show that label-dispersion is a promising predictor of the uncertainty of the network, and show on two benchmark datasets that an active learning algorithm based on label-dispersion obtains excellent results.
Semi supervised learning machine learning made simpleDevansh16
Video: https://youtu.be/65RV3O4UR3w
Semi-Supervised Learning is a technique that combines the benefits of supervised learning (performance, intuitiveness) with the ability to use cheap unlabeled data (unsupervised learning). With all the cheap data available, Semi Supervised Learning will get bigger in the coming months. This episode of Machine Learning Made Simple will go into SSL, how it works, transduction vs induction, the assumptions SSL algorithms make, and how SSL compares to human learning.
About Machine Learning Made Simple:
Machine Learning Made Simple is a playlist that aims to break down complex Machine Learning and AI topics into digestible videos. With this playlist, you can dive head first into the world of ML implementation and/or research. Feel free to drop any feedback you might have down below.
Paper Annotated: SinGAN-Seg: Synthetic Training Data Generation for Medical I...Devansh16
YouTube video: https://www.youtube.com/watch?v=Ao-19L0sLOI
SinGAN-Seg: Synthetic Training Data Generation for Medical Image Segmentation
Vajira Thambawita, Pegah Salehi, Sajad Amouei Sheshkal, Steven A. Hicks, Hugo L.Hammer, Sravanthi Parasa, Thomas de Lange, Pål Halvorsen, Michael A. Riegler
Processing medical data to find abnormalities is a time-consuming and costly task, requiring tremendous efforts from medical experts. Therefore, Ai has become a popular tool for the automatic processing of medical data, acting as a supportive tool for doctors. AI tools highly depend on data for training the models. However, there are several constraints to access to large amounts of medical data to train machine learning algorithms in the medical domain, e.g., due to privacy concerns and the costly, time-consuming medical data annotation process. To address this, in this paper we present a novel synthetic data generation pipeline called SinGAN-Seg to produce synthetic medical data with the corresponding annotated ground truth masks. We show that these synthetic data generation pipelines can be used as an alternative to bypass privacy concerns and as an alternative way to produce artificial segmentation datasets with corresponding ground truth masks to avoid the tedious medical data annotation process. As a proof of concept, we used an open polyp segmentation dataset. By training UNet++ using both the real polyp segmentation dataset and the corresponding synthetic dataset generated from the SinGAN-Seg pipeline, we show that the synthetic data can achieve a very close performance to the real data when the real segmentation datasets are large enough. In addition, we show that synthetic data generated from the SinGAN-Seg pipeline improving the performance of segmentation algorithms when the training dataset is very small. Since our SinGAN-Seg pipeline is applicable for any medical dataset, this pipeline can be used with any other segmentation datasets.
Subjects: Image and Video Processing (eess.IV); Computer Vision and Pattern Recognition (cs.CV); Machine Learning (cs.LG)
Cite as: arXiv:2107.00471 [eess.IV]
(or arXiv:2107.00471v1 [eess.IV] for this version)
Reach out to me:
Check out my other articles on Medium. : https://machine-learning-made-simple....
My YouTube: https://rb.gy/88iwdd
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A simple framework for contrastive learning of visual representationsDevansh16
Link: https://machine-learning-made-simple.medium.com/learnings-from-simclr-a-framework-contrastive-learning-for-visual-representations-6c145a5d8e99
If you'd like to discuss something, text me on LinkedIn, IG, or Twitter. To support me, please use my referral link to Robinhood. It's completely free, and we both get a free stock. Not using it is literally losing out on free money.
Check out my other articles on Medium. : https://rb.gy/zn1aiu
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Reach out to me on LinkedIn. Let's connect: https://rb.gy/m5ok2y
My Instagram: https://rb.gy/gmvuy9
My Twitter: https://twitter.com/Machine01776819
My Substack: https://devanshacc.substack.com/
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Get a free stock on Robinhood: https://join.robinhood.com/fnud75
This paper presents SimCLR: a simple framework for contrastive learning of visual representations. We simplify recently proposed contrastive self-supervised learning algorithms without requiring specialized architectures or a memory bank. In order to understand what enables the contrastive prediction tasks to learn useful representations, we systematically study the major components of our framework. We show that (1) composition of data augmentations plays a critical role in defining effective predictive tasks, (2) introducing a learnable nonlinear transformation between the representation and the contrastive loss substantially improves the quality of the learned representations, and (3) contrastive learning benefits from larger batch sizes and more training steps compared to supervised learning. By combining these findings, we are able to considerably outperform previous methods for self-supervised and semi-supervised learning on ImageNet. A linear classifier trained on self-supervised representations learned by SimCLR achieves 76.5% top-1 accuracy, which is a 7% relative improvement over previous state-of-the-art, matching the performance of a supervised ResNet-50. When fine-tuned on only 1% of the labels, we achieve 85.8% top-5 accuracy, outperforming AlexNet with 100X fewer labels.
Comments: ICML'2020. Code and pretrained models at this https URL
Subjects: Machine Learning (cs.LG); Computer Vision and Pattern Recognition (cs.CV); Machine Learning (stat.ML)
Cite as: arXiv:2002.05709 [cs.LG]
(or arXiv:2002.05709v3 [cs.LG] for this version)
Submission history
From: Ting Chen [view email]
[v1] Thu, 13 Feb 2020 18:50:45 UTC (5,093 KB)
[v2] Mon, 30 Mar 2020 15:32:51 UTC (5,047 KB)
[v3] Wed, 1 Jul 2020 00:09:08 UTC (5,829 KB)
This slide deck goes over the concept of recurrence relations and uses that to build-up to the concept of the Big O notation in computer science, math, and asymptotic analysis of algorithms.
Paper Explained: One Pixel Attack for Fooling Deep Neural NetworksDevansh16
Read more: https://devanshverma425.medium.com/what-should-we-learn-from-the-one-pixel-attack-a67c9a33e2a4
Abstract—Recent research has revealed that the output of Deep
Neural Networks (DNN) can be easily altered by adding relatively small perturbations to the input vector. In this paper, we analyze an attack in an extremely limited scenario where only one pixel can be modified. For that we propose a novel method for generating one-pixel adversarial perturbations based on differential evolution (DE). It requires less adversarial information (a blackbox attack) and can fool more types of networks due to the inherent features of DE. The results show that 67.97% of the natural images in Kaggle CIFAR-10 test dataset and 16.04% of the ImageNet (ILSVRC 2012) test images can be perturbed to at least one target class by modifying just one pixel with 74.03% and 22.91% confidence on average. We also show the same vulnerability on the original CIFAR-10 dataset. Thus, the proposed attack explores a different take on adversarial machine learning in an extreme limited scenario, showing that current DNNs are also vulnerable to such low dimension attacks. Besides, we also illustrate an important application of DE (or broadly speaking, evolutionary computation) in the domain of adversarial machine learning: creating tools that can effectively generate lowcost adversarial attacks against neural networks for evaluating robustness.
Check out my other articles on Medium. : https://rb.gy/zn1aiu
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Reach out to me on LinkedIn. Let’s connect: https://rb.gy/m5ok2y
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Paper Explained: Understanding the wiring evolution in differentiable neural ...Devansh16
Read my Explanation of the Paper here: https://medium.com/@devanshverma425/why-and-how-is-neural-architecture-search-is-biased-778763d03f38?sk=e16a3e54d6c26090a6b28f7420d3f6f7
Abstract: Controversy exists on whether differentiable neural architecture search methods discover wiring topology effectively. To understand how wiring topology evolves, we study the underlying mechanism of several existing differentiable NAS frameworks. Our investigation is motivated by three observed searching patterns of differentiable NAS: 1) they search by growing instead of pruning; 2) wider networks are more preferred than deeper ones; 3) no edges are selected in bi-level optimization. To anatomize these phenomena, we propose a unified view on searching algorithms of existing frameworks, transferring the global optimization to local cost minimization. Based on this reformulation, we conduct empirical and theoretical analyses, revealing implicit inductive biases in the cost's assignment mechanism and evolution dynamics that cause the observed phenomena. These biases indicate strong discrimination towards certain topologies. To this end, we pose questions that future differentiable methods for neural wiring discovery need to confront, hoping to evoke a discussion and rethinking on how much bias has been enforced implicitly in existing NAS methods.
Paper Explained: RandAugment: Practical automated data augmentation with a re...Devansh16
RandAugment: Practical automated data augmentation with a reduced search space is a paper that proposes a new Data Augmentation technique that outperforms all current techniques while being cheaper.
Learning with noisy labels is a common challenge in supervised learning. Existing approaches often require practitioners to specify noise rates, i.e., a set of parameters controlling the severity of label noises in the problem, and the specifications are either assumed to be given or estimated using additional steps. In this work, we introduce a new family of loss functions that we name as peer loss functions, which enables learning from noisy labels and does not require a priori specification of the noise rates. Peer loss functions work within the standard empirical risk minimization (ERM) framework. We show that, under mild conditions, performing ERM with peer loss functions on the noisy dataset leads to the optimal or a near-optimal classifier as if performing ERM over the clean training data, which we do not have access to. We pair our results with an extensive set of experiments. Peer loss provides a way to simplify model development when facing potentially noisy training labels, and can be promoted as a robust candidate loss function in such situations.
Found this paper really interesting. It delves into the learning behaviors of Deep Learning Ensembles and compares them Bayesian Neural Networks, which theoretically does the same thing. This answers why Deep Ensembles Outperform
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
State of Artificial intelligence Report 2023kuntobimo2016
Artificial intelligence (AI) is a multidisciplinary field of science and engineering whose goal is to create intelligent machines.
We believe that AI will be a force multiplier on technological progress in our increasingly digital, data-driven world. This is because everything around us today, ranging from culture to consumer products, is a product of intelligence.
The State of AI Report is now in its sixth year. Consider this report as a compilation of the most interesting things we’ve seen with a goal of triggering an informed conversation about the state of AI and its implication for the future.
We consider the following key dimensions in our report:
Research: Technology breakthroughs and their capabilities.
Industry: Areas of commercial application for AI and its business impact.
Politics: Regulation of AI, its economic implications and the evolving geopolitics of AI.
Safety: Identifying and mitigating catastrophic risks that highly-capable future AI systems could pose to us.
Predictions: What we believe will happen in the next 12 months and a 2022 performance review to keep us honest.
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
Learn SQL from basic queries to Advance queriesmanishkhaire30
Dive into the world of data analysis with our comprehensive guide on mastering SQL! This presentation offers a practical approach to learning SQL, focusing on real-world applications and hands-on practice. Whether you're a beginner or looking to sharpen your skills, this guide provides the tools you need to extract, analyze, and interpret data effectively.
Key Highlights:
Foundations of SQL: Understand the basics of SQL, including data retrieval, filtering, and aggregation.
Advanced Queries: Learn to craft complex queries to uncover deep insights from your data.
Data Trends and Patterns: Discover how to identify and interpret trends and patterns in your datasets.
Practical Examples: Follow step-by-step examples to apply SQL techniques in real-world scenarios.
Actionable Insights: Gain the skills to derive actionable insights that drive informed decision-making.
Join us on this journey to enhance your data analysis capabilities and unlock the full potential of SQL. Perfect for data enthusiasts, analysts, and anyone eager to harness the power of data!
#DataAnalysis #SQL #LearningSQL #DataInsights #DataScience #Analytics
Predictably Improve Your B2B Tech Company's Performance by Leveraging DataKiwi Creative
Harness the power of AI-backed reports, benchmarking and data analysis to predict trends and detect anomalies in your marketing efforts.
Peter Caputa, CEO at Databox, reveals how you can discover the strategies and tools to increase your growth rate (and margins!).
From metrics to track to data habits to pick up, enhance your reporting for powerful insights to improve your B2B tech company's marketing.
- - -
This is the webinar recording from the June 2024 HubSpot User Group (HUG) for B2B Technology USA.
Watch the video recording at https://youtu.be/5vjwGfPN9lw
Sign up for future HUG events at https://events.hubspot.com/b2b-technology-usa/
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Discussion on Vector Databases, Unstructured Data and AI
https://www.meetup.com/unstructured-data-meetup-new-york/
This meetup is for people working in unstructured data. Speakers will come present about related topics such as vector databases, LLMs, and managing data at scale. The intended audience of this group includes roles like machine learning engineers, data scientists, data engineers, software engineers, and PMs.This meetup was formerly Milvus Meetup, and is sponsored by Zilliz maintainers of Milvus.
Paper Explained: Deep learning framework for measuring the digital strategy of companies from earnings calls
1. Deep Learning Framework for Measuring the Digital Strategy of
Companies from Earnings Calls
Ahmed Ghanim Al-Ali1,2
, Robert Phaal1
, and Donald Sull3
1
Department of Engineering, University of Cambridge, Cambridge, UK
2
DeepOpinion, Innsbruck, Austria
3
Sloan School of Management, MIT, Boston, USA
ahmed.alali@deepopinion.ai, rp108@cam.ac.uk, dsull@mit.edu,
Abstract
Companies today are racing to leverage the latest digital technologies, such as artificial
intelligence, blockchain, and cloud computing. However, many companies report that their
strategies did not achieve the anticipated business results. This study is the first to apply state-
of-the-art NLP models on unstructured data to understand the different clusters of digital
strategy patterns that companies are Adopting. We achieve this by analyzing earnings calls from
Fortune’s Global 500 companies between 2015 and 2019. We use Transformer-based
architecture for text classification which show a better understanding of the conversation
context. We then investigate digital strategy patterns by applying clustering analysis. Our
findings suggest that Fortune 500 companies use four distinct strategies which are product-led,
customer experience-led, service-led, and efficiency-led1
. This work provides an empirical
baseline for companies and researchers to enhance our understanding of the field.
1 Introduction
The use of digital technologies is transforming the modern economy with significant implications for
businesses. As a result, organizations are perceiving digital technologies to present both growth oppor-
tunities and existential threats (Sebastian et al., 2017). Despite efforts to adopt such technologies, re-
search demonstrates that the success rate in improving business performance is very low due to the lack
of a coherent digital strategy (Correani et al., 2020). A positive research step to address this challenge is
enhancing the understanding of current approaches to digital strategy.
Corporate documents are increasingly being used to understand the performance of organizations for
various purposes. Examples are, predicting expected returns from financial reports (Theil et al., 2019)
and measuring compliance from sustainability reports (Smeuninx et al., 2020).
In the present study, we use earnings calls transcripts2
, as they provide rich insights into companies’
activities, specifically on their digital strategy. We quantify the approach taken by companies based on
the progress made on the following three components related to the digital strategy (Vial, 2019):
• Business value: the expressed value of using a specific digital solution (e.g., enhancing customer
experience and increasing operational efficiency)
• Strategy management: the policies and practices in place to support the implementation of digital
solutions (e.g., setup of innovation lab, acquisition of startups, and use of agile methods)
• Digital technology: the technology used as a part of the identified digital solution (e.g., artificial
intelligence, Internet of things, and robotics)
In this work, we offer two contributions. First, we set the baseline for using deep learning based NLP
models to measure the digital strategy of companies from earnings calls transcripts. Second, we apply
this framework to investigate the digital strategy of Fortune’s Global 500 companies.
1
Experiment repository: https://github.com/alali3030/earnings_calls_NLP
2
A voice or videoconference calls held by a public company to discuss financial results for a given financial period. These
calls are recorded and transcribed to be accessible for investors and the public.
2. 2 Related Work
There have been a few recommendations for the digital strategy to be customer focused, product focused
(Sebastian et al., 2017), or business model focused (Vial, 2019). However, an empirical investigation of
digital strategy archetypes is still needed (Tekic & Koroteev, 2019).
A few NLP-driven publications have investigated the digital strategy of companies. This included
network analytics of website tags (Stoehr et al., 2019), document clustering of companies’ description
(Riasanow et al., 2020), and keyword analysis of financial reports (Pramanik et al., 2019). While all
these studies revealed insights into the digital strategy of companies, they were exploratory in nature
with limited quantitative evaluation of digital strategy components.
Earnings calls transcripts are known to be rich data sources and considered to be more informative
and insightful than company filing (Frankel et al., 1999). Moreover, they can be leveraged for text clas-
sification to identify decisions and activities that companies take (Keith & Stent, 2019). Therefore, we
propose text classification of digital strategy related topics from earnings calls transcripts as detailed in
Section 3.
3 Methodology
There is no generic framework to measure company performance, as it can be topic specific. Measuring
digital strategy retrospectively is accomplished by identifying the progress made on its components, also
known as digital maturity (Gurbaxani & Dunkle, 2019). From an NLP perspective, this requires identi-
fying topics of interest in the text, followed by assigning a maturity score to it. The closest text classifi-
cation task to this is aspect-based sentiment analysis, which is proven to be effective for mining aspects
related to customers’ opinions (Jiang et al., 2019). Therefore, we adapt this task to measure companies’
digital strategy and refer to it as Aspect-based Maturity Analysis (ABMA).
In this case, we propose Aspects that refer to 17 coarse-grained topics from the three components of
digital strategy presented in the introduction (business value [4 aspects], strategy management [2 as-
pects], and digital technology [11 aspects]). The design and selection on the 17 topics was based on
extensive literature review of various publications on digital strategy components (Al-Ali, 2020). We
find multi-label classification suitable as the labels are not mutually exclusive. Maturity, on the other
hand, refers to the progress made with a given aspect over four discrete steps, including (1) plan, (2)
pilot, (3) release, and (4) pioneer (EY & Microsoft, 2019). We propose the use of multi-class classifica-
tion given that maturity runs on a discrete scale. Model labels are shown in Table 1. See Appendix B for
the list of labels definitions. The following is an example of the classification process from the earnings
calls dataset:
TEXT: “We’re putting most of our efforts right now—are continuing to—into our robotics program.
We think it’s been a great addition to our fulfillment capacity.”
{Aspects: [robotics, operations], Maturity: released (3)}
Task Labels
Aspect
Business Value: digital products, digital customer experience, digital operations, digital
business model
Strategy Management: strategy enablers, strategy practices
Digital technologies: AI, analytics, Internet of things, blockchain, cloud computing, mo-
bile, social media, robotics, augmented reality, virtual reality, 3D printing
Maturity Plan, Pilot, Release, Pioneer
4 Experiment Setup
The objective of the experiment is to demonstrate the utility of ABMA in measuring the digital strategy
of Fortune 500 companies using earnings calls transcripts. The process included pre-processing and
Table 1: Labels description for Aspect and Maturity classification.
3. structuring the text, filtering irrelevant content, classifying the text, and aggregating the results to the
company level. We then clustered the results in Section 5 to identify common digital strategy patterns.
4.1 Data and Pre-processing
We chose Fortune’s Global 500 companies as a suitable sample based on their diversity and scale of
digital activities (Fortune.com, 2019). Our data consists of 4,911 earnings calls transcripts for 304 com-
panies covering the five years between January 1, 2015 and December 31, 2019. 195 companies were
excluded due to missing or inconsistent data from the source. The data was then tabularized with fea-
tures, including company name, ticker symbol, date of call, and call transcript.
Performing sentence-level splitting resulted in approximately 3.2 million sentences. We conducted a
keyword search to select relevant sentences and maintain a dense dataset. The keywords included 275
domain-specific terms3
from the 17 topics related to the three digital strategy components. This resulted
in 46,277 sentences showing that around 1.46% of earning calls discussions are digital related. We also
added previous and following sentences to capture sufficient context. We refer to each text block as a
document.
4.2 Text Classification
Based on the proposed approach, we designed two-stage text classification architectures. The first model
is multi-label to detect the occurrence of an aspect in a document, whereas the second model assigns a
maturity class to it4
. As an experiment, we hand-annotated 1,300 examples from a random sample on
aspects and their respective maturity levels as shown by the illustrative example in Section 3. We split
the labeled data to 80/10/10 between training, validation, and testing respectively.
Given the absence of a benchmark, we compared the performance of several text classification mod-
els, including transformer architecture. We trained the transformer models by applying a discriminative
classification fine-tuning to maximize the utilization of the language model pre-training (Howard &
Ruder, 2018). The training process also included gradual unfreeze of each layer with a slanted triangular
learning rate to aid the convergence of the model parameters towards task-specific features (Howard &
Ruder, 2018). We found that the pretrained RoBERTa (Liu et al., 2019) performed best without further
language model fine-tuning, as shown in Table 2. The main difference was that RoBERTa was able to
achieve higher accuracy on scarce labels. Moreover, we found RoBERTa to generalize better based on
context with unseen terminologies. The qualitative evaluation of the output showed reasonable perfor-
mance based on the training dataset size, in which errors were commonly attributed to imprecisely ex-
pressed sentences.
Model
Aspect Maturity
Precision Recall F1-weighted Precision Recall F1-weighted
RoBERTa base 68.9 67.5 67.4 59.1 58.2 58.2
BERT base 65.5 63.3 62.0 56.8 56.0 55.7
LSTM+GloVe 66.4 60.2 62.5 51.3 50.9 50.6
NB SVM 52.1 46.0 47.0 49.0 51.3 49.0
Table 2: Aspect and Maturity experiment results.
4.3 Processing Output
Using the described text classification approach, we detected 61,872 aspect occurrences in 27,198 docu-
ments on 295 companies. This shows that 58.7% of the filtered dataset referred to a specific digital strategy-
related activity by the company.
To aggregate results from the documents to the company level, we applied several transformation steps.
First, we one-hot encoded all the aspects to obtain a binary feature vector. Second, we multiplied each
vector of a document with its respective maturity class (1–4).
Differentiating companies that exhibit multiple maturity levels of an aspect in the same year was im-
portant. Taking a weighted average was penalizing companies for simultaneous maturity levels. Therefore,
3
Appendix A provides a list of the keyword terms for each label.
4
Appendix B outlines the classification labels definitions, annotation process, and label count in the dataset.
4. we treat the maturity of an aspect as a checklist, in which the score is calculated by summing each identified
maturity class within the same year for a given aspect. We then calculated the mean across the five years,
which resulted in a maturity score between 0 and 10 for each aspect. As a result, the dataset was a matrix
of 295 companies × 18 features (17 aspects-maturity scores + mean maturity).
5 Clustering of Results
Companies may adopt various digital strategies based on sector, digital maturity, and business scope.
To identify the common digital strategy archetypes, we clustered the data. As k-means clustering as-
sumes an equal mean and variance, we standardized the data by applying MinMax scaling and log trans-
formation. There were few sparse features, so we chose 12 dense features (non-zero values > 40% of all
companies). We also applied t-SNE5
for dimensionality reduction, as it significantly improved clustering
performance (Maaten & Hinton, 2008). Plotting the Silhouette score for clustering showed multiple
peaks demonstrating inherent hierarchy in the data. Upon visual inspection, we found 10 clusters to be
meaningful representation. The cluster map is illustrated in Figure 1 (a).
Investigating the cluster map revealed two main insights. First, clusters generally included companies
in the same or a related sector. This indicates that the digital strategy can be sector specific. Second, we
found a few companies from various sector clustered with predominantly digital native companies from
the technology sector. Some examples are ABB and Siemens from the industrial sector are in cluster 2
due to their capabilities in automation and robotics technologies while the majority of their peer compa-
nies are in cluster 6. This indicates that some companies have made significant progress in digitally
transforming their business.
We investigate the clusters by calculating the mean maturity value for each feature across the 10
clusters. We found four distinct digital strategies shared between eight clusters, whereas the remaining
two had very limited digital maturity. The four digital strategy archetypes are product led (cluster 2),
customer experience led (cluster 4), service led (clusters 0,7,8,9), and efficiency led (clusters 3,6), as
illustrated by the radar charts in Figure 1 (b). We also found that while companies lead with a specific
business value, such as customer experience, the vast majority demonstrate some level of progress across
all areas. Therefore, focusing on a single area, as some authors argue, might not be practical due to the
interdependencies between business functions (Sebastian et al., 2017; Westerman et al., 2014).
Our findings have two main implications. First, managers can use the identified archetypes as a base-
line for digital strategy formulation and as a tool to benchmark the progress made against relevant com-
panies. Second, researchers can build on our findings to investigate digital strategy further.
5
t-SNE hyperparameters were set as (n dimensions=2, random state=42, perplexity=10, learning rate = 200, iterations=1000)
Cluster 2 - Tech Pioneers Cluster 4 – Digital Experience
Cluster 6 – Industry 4.0 Cluster 8 – Brick & Mobile
(a) Cluster Map
Cluster 2
Cluster 4
Cluster 6
Cluster 8
(b) Radar Charts
Figure 1: illustration of the digital strategy clusters
(a) Cluster map of the 295 companies based on digital strategy similarity (b) Radar chart of the main 4 archetypes
5. 6 Conclusion
In this study, we present a deep learning framework for measuring the digital strategy of companies by
using earnings calls transcripts. In the process, we demonstrate the practical value of state-of-the-art
NLP models beyond inference. The results from our experiment enhance the understanding of digital
strategy by identifying four distinct digital strategy archetypes. Our findings may serve as a baseline for
companies attempting to formulate or benchmark their digital strategy as well as an empirical foundation
for further research. For future studies, we recommend investigating the causal relationship between
aspect maturity and financial performance.
Acknowledgements
We thank the anonymous reviewers for their helpful feedback. We also thank Tim Pearce, Farah
Shamout, and Adrià Salvador Palau for their insightful and valuable feedback.
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7. Appendix A. List of Keyword Terms
This list presents 17 topics of interest detailed by 350 definitional terms. This list of keyword terms was
used to preselect relevant sentences for analysis.
Topic Keyword Keyword terms
Business Value
Digital Product
smart product*, connected product*, software as a service, Saas,
platform as a service, Paas, platform, product as a service
Digital Customer
Experience
digital experience, customer experience, CX, user experience, UX,
user journey, customer journey, digital engagement, customer
engagement, personalization, personalisation, digital marketing,
recommendation, market place, marketplace, e-commerce platform,
digital service, digital services, e-service, online chat, chatbot, bappb,
digital chnnel, omnichannel
Digital
Operations
process automation, process mining, process analytics, process
optimization, efficiency, cost saving, cost reduction, reduce cost,
reducing cost, automation, predictive maintenance, ERP, supply chain,
logistics, operations
Digital Business
Model
business model, new market, new segment, monitization, Saas,
software as a service, on-demand, product as a service, value
proposition, freemium, subscription, marketplace, ad-revenue, ads,
peer-to-peer, two-sided, double-sided
Strategy
Management
Enablers
digital strategy, digital business strategy, digital transformation
strategy, governance, priositization, prioritization, digital vision,
digital leadership, leadership support, leadership buy-in,
communication, digital goals, data scientist, data analyst machine
learning engineer, developer, coder, programmer, chief digital officer,
CDO, head of digital transformation, head of digital, product manager,
product owner, cross-functional, scrum master, agile coach, innovation
manager, Data lake, data warehouse, middle ware, enterprise
architecture, digital tools, digital workplace, digital integration, chat,
video call, CRM, ERP, service oriented architecture, bSOAb
Practices
Agile, scrum, MVP, minimum viable product, sprint, design thinking,
business experiment, DevOps, bepicb, feature, user story, product
owner, product manager, collaboration, cross functional, cross-
functional, A/B testing, exploratory data analysis, data analysis,
decision support system, dashboard, hypothesis testing, experimental
design, product metrics, user metrics, usage metrics, click through rate,
conversion rate, click stream, digital marketing, customer
segmentation, risk modelling, simulation, decision analytics, decision
support system, project management, digital skills, digital leadership,
transformation, data analysis, social media management, social
listening, user research, UX research, UX design, UI design,
programming, coding, lean startup, experimentation, incubator,
accelerator, innovation lab, digital lab, digital transformation, open
innovation, design thinking, design sprint, digitalization, digitalisation,
digitization, digital technolog[a-z]*
8. Topic Keyword Keyword terms
Digital
Technology
AI
bAIb, artificial intelligence, NLP, natural language processing,
natural language understanding, NLU, natural language generation,
NLG, speech recognition, sentiment analysis, speech to text, text to
speech, deep learning, machine learning, bMLb, neural network,
algorithm, generative adversarial network, GANs, supervised learning,
unsupervised learning, reinforcement learning, semi-supervised
learning, active learning, self learning, transfer learning, back
propogation, tensorflow, Salesforce Einstein, IBM Watson, kaggle, AI
as a service, Microsoft azure ML, AutoML, autonomous vehicles,
computer vision, image recognition, pattern recognition, cognitive
computing, predictive analytics, predictive maintenance, algorithmic
trading, clustering, dimensionality reduction, t-sne, PCA, principal
component analysis, chatbot, bbotb, RPA, robotic process
automation, matrix factorization, collaborative filtering, recommender
system, recommendation engine, graph mining, graph theory, cortana,
alexa, google assistant
Cloud computing
cloud computing, cloud native, cloudless, distributed cloud, distributed
computing, clustered computing, hybrid cloud, platform as a service,
edge computing, cloud api, google cloud, azure cloud, aws cloud,
software as a service, cloud applications, cloud, GPU, HPC
management, cloud storage, elasticity, elastic computing, the cloud,
data platform
IoT
Internet of things, bIoTb, industrial internet, IIoT, embedded device,
embedded sensor, digital twin, digital thread, building information
modelling, BIM, connected devices, connected sensors, IoE, internet
of everything, smart machines, connected machines, wearable, cyber
physical systems, machine to machine, connected factory, model
based definition
Virtual reality bVRb, virtual reality, immersive technologies, mixed reality
Augmented
reality
bARb, augmented reality, immersive technologies, mixed reality
Robotics
robots, humanoid, drone, drones, smart robots, smart warehouse, smart
spaces, Lidar, computer vision, UAV, autonomous vehicles, swarm
robots, industrial robot, robotics, automation
Analytics
analytics, business intelligence, optimization, exploratory data
analysis, data science, augmented analytics, descriptive analytics,
descriptive statistics, prescriptive analytics, predictive, inference,
inferential, customer segmentation, correlation, data visualization, data
storytelling, text analytics, data lake, data warehouse, big data, social
analytics, , network analytics, network mining, network analysis
Mobile
mobile, smart phone, mobile app, mobile application, mobile platform,
mobile solution, mobile technology
Social social media, social network, content marketing
3D printing
3D print[a-z]*, additive manufacturing, 3D scan, material jetting,
stereolithography, bioprint, bioprinted organ, Fused deposition
modeling, Digital Light Processing, Selective Laser Sintering,
Selective laser melting, Laminated object manufacturing, Digital Beam
Melting
Blockchain
blockchain, distributed ledger, decentralized, smart contracts,
cryptocurrency, bICOb, initial coin offering, asset tokenization
9. Appendix B. Definition & Frequency of Labels
This list provides a definition of the labels and their frequency in the whole dataset (training and infer-
ence). The definitions were used to guide the annotation process. All labelling was carried out by the
authors due to the need for domain knowledge in relation to digital strategy.
Group Aspect Keyword definition Count
Business
Value
Digital Product
Enhancing product value through digital features usually
requires integrating a combination of products, services and
data
17,936
Digital Customer
Experience
To create a seamless, omnichannel experience that makes it
easy for customers to order, inquire, pay and receive support in
a consistent way from any channel at any time
5,107
Digital Operations
The technology and business capabilities that ensure the
efficiency, scalability, reliability, quality and predictability of
core operations
3,399
Digital Business
Model
A significantly new way of creating and capturing business
value that is embodied in or enabled by digital technologies
1,105
Strategy
Management
Enablers
All measures that a company have in place to become digitally
enabled such as digital strategy, technological infrastructure,
and governance
11,035
Practices
All activities that reflects digital maturity such as agile
practices, data-driven decision making, and digital innovation
2,245
Digital
Technology
AI
Only the explicit mention of digital technologies using com-
mercial or technical terms was used in labelling and inference.
Therefore, no definition was needed for this task.
2,897
Cloud computing 3,931
IoT 1,565
Virtual reality 290
Augmented reality 223
Robotics 1,509
Analytics 2,916
Mobile 6,502
Social 773
3D printing 26
Blockchain 413
Maturity Definition Count
Plan Digital initiative is or being planned 4,286
Pilot Digital initiative is being developed or piloted 14,220
Release Digital initiative is launched and making active contribution to the business 12,115
Advance Digital initiative is being pioneered and making significant business impact 1,3754