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- 1. Why: We will be evaluating both academic and personal perspectives of leadership. Doing this assignment helps you to analyze leadership practices by researching a personal perspective of a leader you believe was/is extraordinary and showing how the readings inform your leadership development and professional experience. o How: Complete or review the readings, videos, and instructor lectures for weeks through the week the assignment is due. Select an extraordinary leader that you would like to learn more about, someone whom you may know and gain access. Consider individuals who in some ways have made positive contributions to society, including both men and women. The leader you select may be from any walk of life (business, the arts, humanities, politics, etc.) Ask for an opportunity to conduct a phone, email or in-person interview. Consider selecting a person at your work, a professor or Northeastern community member, anyone who has a compelling story to tell about leadership. Create a preliminary list of open-ended questions to ask the person that you are profiling. Conduct the interview with the person you select. Prepare an analysis of this leader that includes the following information and connects to our readings and class learning: o Key Events: A short summary of the key events in this leaderâ s life that may have had an impact on his/her approach to leadership. Note: This is an analysis â not a biography.
- 2. o Leadership Approach: Analyze your leader integrating the readings and key learning from class. Areas that your analysis should include but be limited to: o How does this leader exemplify effective leadership? Provide specific evidence for your claims. o How does this leader demonstrate certain specific leadership practices or perspectives we covered in our text and readings and discussion? o How did this leader sustain commitment and build trusting partnerships? o What were mistakes or missteps that were valuable lessons about leadership for this person? o Principles and Values: What espoused principles and values guide their approach as a leader? How are these principles or values apparent to those s/he leads? How were those values formed? o Response to Challenges: Has the leader faced significant challenges that demanded leadership? How did they react to these challenges? What do those actions say (to the Learning Team) about their leadership ability? o Results: What significant results were they able to achieve? How did their approach to leadership contribute to their results? 26/02/20 1 Measuring Consumer Behaviour Part I
- 3. Week 5 Required readings Extract from another textbook (available on FLO): “Conducting research in consumer behaviour”, in Hoyer, W. D,, Macinnis, D., Pieters, R., Chan, E., and Northey, G. (2018) Consumer Behaviour, Asia- Pacific Edition, Cengage Learning, pp.36-48 . Learning objectives • To understand the importance of measuring consumer behaviour and the different approaches to it • To explain the main types of research methods (and data) that can be used for the measurement of consumer behaviour (primary and secondary) • To understand how to set up a standard consumer survey aimed at evaluating memory and decision-making (at brand-level) 26/02/20 2 Alternative views on consumer behaviour
- 4. • Consumer research can be classified by paradigm, which is the set of assumptions a researcher makes about what they are studying and how they study it. • Positivism (modernism): – Paradigm that emphasises the supremacy of human reason and the objective search for truth through science • Interpretivism (postmodernism): – Paradigm that emphasises the importance of symbolic, subjective experience and the idea that meaning is in the mind of the person Why measuring consumer behaviour? Food for thoughts: What carries more insights? A. Factual knowledge: who, what, when B. Theoretical explanations: why C. A combination of A & B But, can A and B be combined?
- 5. 26/02/20 3 Issue • The measurement of consumer behaviour (positivist view) and the focus on the theoretical explanation of it (interpretivist view) are often SEPARATE • They both offer different insights/advantages; thus being familiar with both ‘views’ provides you with a more holistic take on consumer behaviour (hence why we deal with both in this topic!) So…Why measuring cb? • Objective and scientific (facts, not ‘stories’) • Helps identifying measurable trends (expectations), which leads to forecasting and setting of practical guidelines • Accountability and more straightforward link with managerial decisions and actions (e.g., marketing strategies) CB research methods • Primary – managers collect data via surveys, focus groups, experiments etc. to support their decisions and operations • Secondary – managers use data collected by other entities (e.g., governments and
- 6. agencies) to support their decisions and operations 26/02/20 4 • Surveys • Focus groups and interviews • Storytelling, pictures and diaries • Experiments (incl. field experiments) • Conjoint analysis • Observations and ethnographic research • Purchase panels • Database analysis and netnography • Psychophysiological reactions (neuroscience) Primary CB research tools Focus groups and interviews (qualitative research) • Focus groups – small group of consumers discussing a particular issue guided by a trained moderator in a controlled setting (6-8 participants is quite typical) • Interviews – one to one discussion with a trained interviewer around a particular issues (structured or semi-structured Q&As)
- 7. Data is then transcribed at analyzed in terms of recurring themes/answers (narratives are extracted) Storytelling, pictures and diaries (qualitative research) • Storytelling – consumers are asked to tell stories about their usage experiences • Pictures/photos – consumers are asked to draw pictures or take photos about their usage experiences to explain/remember them • Diaries – consumers are asked to keep a diary of their usage experiences over a certain time period Data is then transcribed at analyzed in terms of recurring themes/answers (narratives are extracted) 26/02/20 5 Experiments (incl. field) (quantitative research) • Experiments – consumers are randomly assigned to ‘treatments’ (e.g., they are showed different packaging) and researchers observe the effects of these treatments on an independent variable of interest (e.g., attitudes towards packaging or
- 8. intention to buy) by means of comparison between (or within) the various groups • Field experiments – e.g., test market Conjoint analysis (quantitative research) • Conjoint analysis – Mix between a survey and an experiment (sophisticated technique) • Aimed at determining the relative importance and appeal of different levels of an offering’s attribute (e.g., different prices, different flavors, different models etc.), which is used to predict consumer choice odds 26/02/20 6 Database and netnography (quantitative and qualitative) • Data mining – i.e., extracting information from customers’ database, looking for patterns and insights • Netnography – tracking online activity, and social media interactions and feelings
- 9. Observations and ethnographic research (qualitative research) • Observing consumers at home, in stores or in service delivery environments to gain some insights • Ethnographic research – includes a combination of observation and in-depth interviews in real-world settings Psychophysiological reactions and neuroscience (quantitative research) • Examining physiological reactions (e.g., eye movements) and applying neuroscience techniques (e.g., measuring brain activity) to understand consumer behaviour 26/02/20 7 Focus in this topic: • Surveys – Week 5
- 10. • Purchase panels – Week 6 Surveys (quantitative research) • In-depth analysis around specific consumer behaviour issues, such as buying behaviour patterns, perceptions of brands, attitudes, media usage and reception, customer satisfaction etc. • Pre-determined set of questions, whereby the answers are used to draw quantitative conclusions about a target population of consumers • Can be conducted in many ways – e.g., face-to- face, over the phone, online 26/02/20 8 A word on design: Definition of the research problem Information required Sampling Survey method (e.g., online, phone etc.) Planning stage Design stage
- 11. Pilot stage Sampling Define the population Determine Sample size Search for sampling frame Specify sampling method Select the sample • Probability (random or stratified) • Non-probability (quota or convenience) Linked to significance of results (larger samples might inflate significance) /Mobile 26/02/20
- 12. 9 Online surveying tools • Qualtrics • Surveymonkey • Zoho • Surveyplanet • …. Ordering of topics Type of questions Wording and instructions Layout Scaling Probes and prompts Coding Planning stage Design stage Pilot stage Type of questions • YES/NO questions (e.g., “Did you visit any of our stores in the past four weeks?” • Multiple choice questions (e.g., for demographic questions such as gender, age, etc.) • Multiple response questions (e.g., for questions asking consumers to associate a brand to certain features, such as ‘good value for money’)
- 13. • Scales and rating/ranking questions (e.g., for attitudes and satisfaction measurements, asking consumers their level of agreement with certain statements) • Open end questions (e.g., asking for suggestions for improvement) 26/02/20 10 Pilot testing Redesign if required Final questionnaire Planning stage Design stage Pilot stage Limitations • Bound by response bias (e.g., random responses or missing responses) and sample size limitations (a few hundreds if lucky, in AU average cost p/p is $3,50-4,50 depending on demographic profile) • A lot of thoughts to be placed on research design, including the wording/format of the questions used
- 14. • Capture stated as opposed to revealed behaviour, which can lead to social desirability bias (main limitation) In a typical CB survey 1. Demographic profile 2. Sample characteristics in relation to the CB aspect examined (e.g., pre-existing level of product expertise, current usage, pre-existing beliefs) 3. Specific questions aimed at uncovering and evaluating specific aspects of the decision-making process (simplification and proxies) 4. Outcome variables – e.g., purchase intentions, stated choices, attitudes (often measured at brand level) 26/02/20 11 [Comparison of various brands within the same market, for more strategic insights] Screening 1. Introduction – i.e., explain general purpose of the survey and reassure about confidentiality
- 15. – “Thank you for agreeing to participate to this survey. It is part of project conducted at Flinders University aimed at…We are interested in your spontaneous views about … and your answers will be strictly anonymous…” – Then ask to Agree/disagree to continue with the survey (informed consent) Screening cont. 2. Demographic profile (can also go at the end) – Age – Household structure – Income – Level of education – Etc. NOTE: always give ranges to choose from (e.g,. “18-25, 25-35 etc.”) and include a “prefer not to say” option in all demographic questions to respect diversity 26/02/20 12 Screening cont. 3. Current level of usage (established behaviour): – For the product/service category or market considered (e.g., toothpaste) “Have you bought toothpaste in the
- 16. past four weeks?” – For a number of brands within the product/service category or market considered “Considering the following brands [LIST], please indicate which brands you have used/bought in the past four weeks” Awareness (recognition) 4. UNAIDED: • “When you think of toothpaste, what is the FIRST brand of toothpaste that comes to mind?” _________ • “What OTHER toothpastes, can you think of?” ________ 5. AIDED: • “Here are some pack shots of some brands of toothpaste [VISUAL STIMULI PROMPTED, such as logos]. Please indicate the brands that you know, even if you only know them by name and have never used them.” 6. Image (retrieval) “Which of these brands do you think each of the following statements apply to? Please select as many or as few of these brands as you feel.” ARM & HAMMER AQUAFRESH COLGATE CREST SENSODYNE Other Don’t Know Leaves my mouth feeling clean O O O O O O O Is the best brand at whitening
- 17. teeth O O O O O O O Provides the best protection against cavities O O O O O O O Keeps my teeth strong and healthy O O O O O O O Meets all my daily toothpaste needs O O O O O O O Has a taste I like O O O O O O O Leaves my breath fresh O O O O O O O Prevents gum problems O O O O O O O Works all day O O O O O O O Eliminates germs on teeth and gums O O O O O O O Is suitable for the whole family O O O O O O O Is an innovative brand O O O O O O O Is worth paying more for O O O O O O O Recommended by dentists/hygienists O O O O O O O Is a brand for someone like me O O O O O O O Strengthens the enamel on my teeth O O O O O O O
- 18. Is a brand I usually buy on sale or with a coupon O O O O O O O Relieves sensitive teeth O O O O O O O Note: this is a ‘pick-any’ format, scales may also be used 26/02/20 13 7. Purchase intention SCALE (e.g., 5, 7 or 11 points): • “On a scale ranging from 0 being extremely unlikely and 10 being extremely likely, what is the chance that you will purchase toothpaste in the near future?” 8. Other elements • Checking for advertising exposure (exposed/not exposed, which media, how recently) • Checking for receptiveness to other marketing stimuli (e.g., bought on promotion) • Consumption occasions (e.g., bought for yourself or others) • Perceptions and attitudes • Explore other outcome behaviours (e.g., likelihood to
- 19. recommend to others, satisfaction etc.) • Explore motives for buying/benefits sought (e.g., bought for specific health needs or reasons) Wording is important • Clear and not ambiguous • Simple, with no jargon • Give options to choose from • Use prompts wisely • Think carefully about your scales • Gather only needed information (be parsimonious), but don’t forget crucial screening and valuable insights • Questions must directly answer the research objectives • Maintain impartiality of questions (no probing) • Sensitive questions must always give a “Prefer not to say” and/or “Other ______ (please specify)” options • Quality over quantity, but make sure you gather ALL information required 26/02/20 14 Bad examples • “We want to know about your ability to recognise previous exposure to an advert and whether that is affecting your level of brand
- 20. knowledge.” • “To what extent do you look for information internally?” • “Please choose between the following options: Reasonably sure, somewhat sure, pretty much sure, sure” Team activity 1 1. Your market to examine is Australian banks. Identify a list of brands of Australian banks to examine and compare (do some quick online research). 2. Draft in Word a consumer survey featuring max 20 questions, following the template given in these handouts 3. Practice the survey within your team and seek feedback from your lecturer to make sure that it is well structured 4. Choose 10 key questions and load your survey online in SurveyMonkey (cannot load for free more than 10 questions) 5. Submit your full-length survey in Word on FLO for marking and email your SurveyMonkey link to your lecturer OPTIONAL FOR EXTRA MARKS:
- 21. • Get some responses and make an attempt to interpret results (include these with your submission) Measuring consumer behaviour Part II Next… 26/02/20 1 Measuring Consumer Behaviour Part II Week 6 Required readings In-class handouts Ehrenberg, A. S. (1995). Empirical generalisations, theory, and method. Marketing Science, 14(3), 20-28. Uncles, M & Wright, M. (2004). Empirical generalisation in marketing, Australasian Marketing Journal, vol. 12, no. 3, pp. 5-18. Ehrenberg, A. S. C., Uncles, M. D., & Goodhardt, G. G. (2004). Understanding brand performance measures: Using Dirichlet
- 22. benchmarks. Journal of Business Research, 57(12), 1307–1325. Learning objectives • To understand the importance of measuring consumer behaviour and the different approaches to it • To explain how to measure consumer buying behaviour through purchase panel data • To discuss the most important known patterns and expectations in consumer buying behaviour • To discuss the importance of empirical generalisations and mathematical models of consumer behaviour • To practice the analysis of purchase panel data 26/02/20 2 Purchase panel data • Records of individual consumers’ purchases over a certain period of time for all products/brands in a market • Large samples of consumers (thousands)
- 23. • ‘Revealed’ choice (real purchases made by consumers) In the 1950’s Andrew Ehrenberg, marketing scientist, started analyzing UK purchase panel data and noticed that: • Consumer buying behaviour showed great variation at individual consumer level, yet was very stable recurring trends/patterns at aggregate level • These characteristics of consumer buying behaviour strongly affected the effectiveness of business strategies (and vice versa) Usefulness So…Why using this? • Objective and scientific (facts, not ‘stories’) • Helps identifying measurable trends (expectations), which leads to forecasting and setting of practical guidelines • Useful to originate data-driven theories, i.e. empirical generalisations 26/02/20 3 Empirical generalisations
- 24. • Recurring trends/patterns emerging across a wide range of conditions or contexts (e.g., across a wide range of different markets) – Supported by empirical evidence (analysis of purchase panel data over time) – Can be explained through quantification (mathematical expressions or formalized statistical models) – Can be used for benchmarking and forecasting Total sales for each individual brand (sum of the values in each column) Total category purchases by each shopper (sum of values in each row) Total CATEGORY sales Snapshot of panel data (e.g., spreads): Measures obtained from panel data Brand Size Brand Loyalty Market Share (%) Penetration (%) Average Purchase Frequency
- 25. Category Buying Rate Share of Category Requirement (%) Derived from the counts of individual purchases over a specific time frame – e.g., one year or one month 26/02/20 4 30 26 20 16 8 Market Share % Canola Sun Dairy Blend Olive Grove Golden Spread To calculate MS simply take the total brand sales (values in the bottom row of the table) divided by the total category sales MS (%) = sales of a brand / sales of the category * 100
- 26. Market Share (%) PEN (%) = number of buyers / number of shoppers * 100 • Buyers are ACTUAL customers of a brand (people that have bought the brand), whereas shoppers are all POTENTIAL customers in the market • Penetration is a measure of the proportion of people that bought the brand AT LEAST ONCE, in the given time period To calculate penetration, you need to work out how many ‘buyers’ a brand has, so counting the number of people out of the sample of 30 potential buyers who purchased a specific brand That number divided by 30 gives the penetration of each brand Penetration (%) APF = number of purchases of THE BRAND / number of brand buyers NB: it's a FREQUENCY (there is no %) It explains how often - how many times on average brand buyers have
- 27. bought the BRAND To calculate average purchase frequency you simply need the total brand sales (values in the bottom row of the table) divided by the number of brand buyers Average Purchase Frequency 26/02/20 5 CBR = number of purchases of THE CATEGORY made by brand buyers / number of brand buyers NB: it's a RATE (there is no %) It explains how often - how many times on average brand buyers have bought the CATEGORY To calculate category buying rate you simply need the category purchases by each individual brand buyer (pick values from total category purchases column) divided by the number of brand buyers Category Buying Rate
- 28. Calculating CBR: E.g. for Golden Spread: Customer 3 bought GS 4 times, but bought from the category 7 times, it’s the 7 that we’re interested in. Customer 5 bought GS once, but bought from the category 11 times. Again, it’s the 11 that we’re interested in To calculate the top part of CBR formula, you’re simply adding each brand buyer’s category total... 7 + 11 +5 + 4 + so on… SCR (%) = (APF / CBR) * 100 It measures the proportion of category needs/purchases satisfied by a certain brand (it is, in fact, the proportion between how much brand buyers have bought on average of the category and how many of those category purchases were dedicated to a specific brand)
- 29. SCR is extremely simple if you have correctly calculated APF and CBR J Share of Category Requirement (%) 26/02/20 6 What can we understand about consumers buying behaviour through the analysis of the values of these measures over time, in a given market? …consumer s are ‘heterogene ous’ in their choices and preferences …con sume rs buy infreq uently
- 30. and irregu larly o ver tim e …consumers buy different product/services categories at different rates, but brands within a specific category at similar rates …consumers buy more than one brand within a specific category (repertoire buying) KEY PATTERNS KEY PATTERNS Reliable abstractions to predict consumer buying behaviour (output) by relying on these expected patterns (input) 1 + 2 always = 3 Mathematical models
- 31. 26/02/20 7 Key regularities of consumer buying behaviour observable in the measures derived from purchase panel data Predictions of expected brand performance measures Benchmark of current vs. expected trends Statistical distributions simulating these
- 32. regularities Forecasting future trends INPUT: observed measures derived from purchase panel data analyzed over time ‘MATHS’ (software) OUTPUT: theoretical measures (to be compared against observed for managerial insights) The Ehrenberg and Goodhardt repeat purchase model How the software looks like Input data 26/02/20 8 o Mean Absolute Deviations (MADs) are the averages of the deviations (differences) between observed data from the panel and theoretical outputs from the model, once withdrawn the sign o Reasonably small deviations and Mean Absolute Deviations (MADs) represent ‘good fit’ of the model – i.e. representativeness of real purchase patterns and
- 33. brand performance for the market analysed Output data Resulting empirical generalisations 1 of 2 • Double Jeopardy Bigger brands (greater market share/more popular) have more buyers (greater penetration), who are also slightly more loyal (greater purchase frequency and SCR) Smaller brands (smaller market share/less popular) have fewer buyers (lower penetration), who are also slightly less loyal (lower purchase frequency and SCR) How can you spot this in the data? 0.00# 0.50# 1.00# 1.50# 2.00# 2.50#
- 34. 3.00# 3.50# 4.00# 4.50# 5.00# 0.00# 0.05# 0.10# 0.15# 0.20# 0.25# 0.30# 0.35# Purchase) Frequency) Penetra/on)%) Double)Jeopardy)line) 26/02/20 9 Exceptions to the Double Jeopardy Excess loyalty brands (very high market share) – i.e., brands that have many buyers (very high penetration) and very high loyalty (very high purchase frequency and SCR) Niche brands (small market share) – i.e., brands that have few buyers (low penetration), but these buyers are quite loyal (high purchase frequency and SCR)
- 35. Change-of-pace brands (high market share) – i.e., brands that have many buyers (high penetration), but these buyers are not very loyal (low purchase frequency and SCR) Resulting empirical generalisations 2 of 2 • Duplication of Purchase Law Brands share customers with other brands (repertoire buying) in line with their market share (smaller brands are once again penalized) Exceptions to this rule are market partitions, i.e. subgroups of brands that are highly substitutable and catering for specific needs (e.g., diet soft drinks, or gum protection toothpastes) To evaluate the Duplication of Purchase count the proportion of customer sharing of customers, i.e. for each brand’s buyers, see how many have bought the other brands as well BRAND 1 BRAND 2 BRAND 3 BRAND 1 BRAND 2
- 36. BRAND 3 Average Who also bought .. T h o se w h o h av e b o u g h t. . % who also bought = number of buyers of a brand who also bought another brand out of the total number of that brand’s buyers * 100
- 37. Brands need to be reported in line with their size (i.e. bigger brand first row/column, then second biggest brand and then smallest brand) How can you spot this in the data? 26/02/20 10 HOW TO DETERMINE IF THERE IS DUPLICATION OF PURCHASE: (1) ROWS: numbers must decrease (getting smaller) from left to right (2) COLUMNS: numbers must be pretty much in line with the average value in the bottom Note: exceptions from (1) and (2) (e.g., large difference from the average) indicate MARKET PARTITIONS = brands sharing more (or less) than expected customers, given their market share Limitations of panel data • Expensive and hard to access • Data may be chain or retailer specific • The approach takes into consideration only the objective nature of consumer behaviour – all other factors and contingencies are assumed to
- 38. be exogenous and somewhat irrelevant • Longitudinal approach required (i.e., analysis must be carried out regularly over multiple time periods otherwise is pointless) Team activity 2 • Use the Excel data set given to calculate all measures for all brands in the given market (cereals) • Report your results in the template given (see FLO) • Write 150-200 words describing the patterns in the data, highlighting if you see any exception from these patterns 26/02/20 11 Teaching break and mid-semester revision Next… List of brands_CHOCMarsB1SnickersB2Kinder BuenoB3TwixB4Nestle' AeroB5MilkywayB6Cadbury
- 39. CrispelloB7Cadbury Dairy MilkB8KitKatB9Cadbury TwirlB10BoostB11BountyB12LionB13Cadbury TimeoutB14GalaxyB15Cadbury WispaB16FlakeB17YorkieB18Lindor Treat BarB19TeasersB20Cadbury CrunchieB21Cadbury PicnicB22 Panel_Data_CHOCOLATENumber of buyersShopperB1B2B3B4B5B6B7B8B9B10B11B12B13B14B15 B16B17B18B19B20B21B22TOTB1B2B3B4B5B6B7B8B9B10B1 1B12B13B14B15B16B17B18B19B20B21B22130030000001100 06200001329100100000010001100001121000002000000040020 00091000001000000010010000300010000000000200140000170 00100000000001001000040010200000000000001600100010100 00000000000110050000004000000020000200800000010000000 10000100610090000000000100000001110010000000000100000 00700170000010000000100010200010000010000000100010810 10000200000000000000410100001000000000000009002200000 00000000000004001100000000000000000010003470000001001 00000020540011000000100100000010114050012000000000020 00002310100100000000001000001200300001000000130000050 22001000010000001000001013000000050401000000000010000 00001010100000000001403000010600000000000101101000010 10000000000010150100000101011017010100000051010000011 10101010000001621500010131000000000000032110001011000 00000000001700021000000000000000003000110000000000000 00001800000003000080300000401800000001000010100000101 90002000050000010000000800010000100000100000002000000 00700000000000000700000001000000000000002100000000110 00000000000200000000110000000000002240200000210001021 00223201010000011000101100111233000105301000000001200 02510001011010000000010002400100000000000000000001001 00000000000000000002503020000202004000010001401010000 10100100001000261004010019100100000001028100101001100 10000000102700000000000001360010002220000000000000110 01000128000100000000000000000010001000000000000000000 29110000000000004000000061100000000000010000000300000 00020040001000003010000000010010001000001031340100010
- 41. capturing the purchases of chocolate brands for 60 consumers. Although it is not a very large data set, you decided to analyze it to understand a little bit more about CaraMilk’s main competitors and, more generally, consumer behavior in terms of buying chocolate. Using the Excel data provided and considering the content of Week 6 lecture, please complete the following template with the results of your calculations (present your results raked by market share, with the largest/most popular brand at the top). Brands Market share (%) Purchase Penetration (%) Purchase Frequency Average
- 42. Now, please answer the following questions (each question should be approximately 150-200 words and include appropriate in-text referencing). 1. Describe the key patterns that can be observed in the above results. 2. On the basis of the results of your analysis, what key facts about consumer behavior discussed in the lecture could you confirm? 3. Discuss the main advantages and disadvantages of panel data. 4. What are empirical generalizations and why are they important to understanding consumer behavior? Include an example of empirical generalizations discussed in the lecture, which you can see in your calculations. 1 Leader Analysis Paper Template and Notes This document is used to guide your interview process, questions and writing. You are not required to use this outline and template. Introduction: 1. Tell me what is the name of the company for whom you work, what is your current role, and how long have you been in this role?
- 43. Company Name: Current Role: How Long: Tell me a little bit about how you came be in your current position and how many direct and indirect reports you have as a leader. Beliefs, Values/Morals, and Ethics (Chapter 13 and ethics handout) 2. Tell me about a time when you were confronted with an ethical dilemma. What were your guiding beliefs that determined how you approached an ethical decision? How do others perceive you as an ethical leader and on what would you base that perception? [Using a relevant quote – i.e., data - demonstrate both analysis and evaluation of the information/data from the questions above.] Chronosystemic and Microsystemic influences: 3. Who influenced you the most in terms of being a leader and how did they impact who you are as a leader?
- 44. Tell me about a time in your life when you first realized that you could be a real leader. How have you kept that experience a part of who you are as a leader? [Using a relevant quote – i.e., data - demonstrate both analysis and evaluation of the information/data from the questions above.] 2 Leadership traits: (use only a couple sentences from the interview for each question below) 4. According to the research on leadership, higher levels of extraversion (being a person who is outgoing), openness to experience, agreeableness, conscientiousness (dependability and attention to detail), are all associated with better leadership. Which areas do you personally see as important to your leadership and how do these traits influence you to be a better leader in your organization? What are 3 long-term, inherent, qualities (i.e., what you were born with – intelligence, height, etc.) do you have as a leader that impacts the
- 45. willingness of people in your organization to follow you more readily? [Using a relevant quote – i.e., data - demonstrate both analysis and evaluation of the information/data from the questions above. Your analysis should lead you to say where the leader is with respect to these areas and include material from your textbook, research articles, videos, and lectures. Your evaluation should include whether the leader is a “good/bad/indifferent leader – and why you think so.] Skills: 5. Over your years as a leader, what leadership skills (those things you can learn) have you specifically set out to improve and why? What specific steps did you take to improve those areas of your leadership? What was most helpful? What obstacles did you encounter and how did you learn to overcome them? Which of these skills did you find easiest to learn (i.e., you had a real talent for learning)? [Using a relevant quote – i.e., data - demonstrate both analysis
- 46. and evaluation of the information/data from the questions above.] Diversity: 6. Diversity; Gender, Race, Culture, etc. How important to you as a leader that you, the company you work for, and your team value diversity? Tell me about how you as a leader use your position and influence to promote diversity. 3 [Using a relevant quote – i.e., data - demonstrate both analysis and evaluation of the information/data from the questions above.] Leadership approaches (Chapters 5 - 12, and 14 - 16 from your textbook and online course material) 7. Pick two or three leadership approaches from the following list that you use to lead others. - Situational (you as a leader adapt to your subordinates) - Authentic (you are able to be yourself and share who you really are with others) - Adaptive (you as a leader adapt to an event or series of events) - Servant (you as a leader serve your subordinates to help them achieve what they want)
- 47. - Transformational (you are able to get subordinates to perform beyond what they think they can do) - Team (you as a leader get everyone to work together for the betterment of all) How do you use them to help you be a better leader? How do others in your organization view your approaches to leadership? What guiding principles have you adopted to help you lead your team more effectively? And how have you integrated them into your leadership style? [Using a relevant quote – i.e., data - demonstrate both analysis and evaluation of the information/data from the questions above.] Trust: 7. How do you go about fostering “trust” with those who are your leaders? Your peers? And your subordinates? Provide a recent example of how you maintained trust as a leader through how you interacted with someone?
- 48. 4 [Using a relevant quote – i.e., data - demonstrate both analysis and evaluation of the information/data from the questions above.] Mistakes/missteps 8. Everyone makes mistakes as a leader. Tell me about one of your mistakes and what did you learned from that situation that helped you be a better leader today? [Using a relevant quote – i.e., data - demonstrate both analysis and evaluation of the information/data from the questions above.] Response to Challenges 9. Tell me about a time when you faced a significant challenge as a leader. How did you react? What leadership strategy guided you? [Using a relevant quote – i.e., data - demonstrate both analysis and evaluation of the information/data from the questions above.]
- 49. BONUS: Thinking about all the leaders you have known or read about, how would you rate yourself as a leader (use a scale from 0 to 10, with 0 being “Worst Leader Ever” to 10 being “An Exceedingly Great Leader”)? Why did you give yourself this rating? [Using a relevant quote – i.e., data - demonstrate both analysis and evaluation of the information/data from the questions above.] 5 References