Hypotheses in Marketing Science: Literature Review and Publication Audit

We examined three approaches to research in marketing: exploratory hypotheses, dominant hypothesis, and competing hypotheses. Our review of empirical studies on scientific methodology suggests that the use of a single dominant hypothesis lacks objectivity relative to the use of exploratory and competing hypotheses approaches. We then conducted a publication audit of over 1,700 empirical papers in six leading marketing journals during 1984-1999. Of these, 74% used the dominant hypothesis approach, while 13 % used multiple competing hypotheses, and 13% were exploratory. Competing hypotheses were more commonly used for studying methods (25%) than models (17%) and phenomena (7%). Changes in the approach to hypotheses since 1984 have been modest; there was a slight decrease in the percentage of competing hypotheses to 11%, which is plained primarily by an increasing proportion of papers on phenomena. Of the studies based on hypothesis testing, only 11 % described the conditions under which the hypotheses would apply, and dominant hypotheses were below competing hypotheses in this regard. Marketing scientists differed substantially in their opinions about what types of studies should be published and what was published. On average, they did not think dominant hypotheses should be used as often as they were, and they underestimated their use

Effects of portfolio planning methods on decision making: experimental results

Subjects (n = 1015) working individually in the role of managers were asked to choose between investment opportunities that would either double their investment or cause the loss of half of it. Six administrators ran experiments on 27 occasions in six countries over a five-year period. Information about the BCG matrix increased the subjects\u27 likelihood of selecting the project that was clearly less profitable. Of subjects exposed to the BCG matrix, 64% selected the unprofitable investment. Of subjects who used the BCG matrix in their analysis, 87% selected the less profitable investment

Portfolio Planning Methods: Faulty Approach or Faulty Research? A Rejoinder to Making Better Decisions by Wensley

Wensley (1994) makes three key points. First, it is worthwhile to conduct empirical studies of the value of management techniques. Second, managers probably misuse portfolio methods. Third, the Armstrong and Brodie study is flawed. We agree with all three points

Forecasting for Marketing

Research on forecasting is extensive and includes many studies that have tested alternative methods in order to determine which ones are most effective. We review this evidence in order to provide guidelines for forecasting for marketing. The coverage includes intentions, Delphi, role playing, conjoint analysis, judgmental bootstrapping, analogies, extrapolation, rule-based forecasting, expert systems, and econometric methods. We discuss research about which methods are most appropriate to forecast market size, actions of decision makers, market share, sales, and financial outcomes. In general, there is a need for statistical methods that incorporate the manager\u27s domain knowledge. This includes rule-based forecasting, expert systems, and econometric methods. We describe how to choose a forecasting method and provide guidelines for the effective use of forecasts including such procedures as scenarios

Forecasting Methods for Marketing: Review of Empirical Research

This paper reviews the empirical research on forecasting in marketing. In addition, it presents results from some small scale surveys. We offer a framework for discussing forecasts in the area of marketing,and then review the literature in light of that framework. Particular emphasis is given to a pragmatic interpretation of the literature and findings. Suggestions are made on what research is needed

Celebrity abuse on Twitter: the impact of tweet valence, volume of abuse, and dark triad personality factors on victim blaming and perceptions of severity

Celebrities are increasingly utilizing social media platforms to establish their brand and interact with their fan base, but in doing so they often become the targets of online abuse. While such abusive acts are known to cause severe consequences in the general population little is known about how celebrity abuse is perceived by observers. This study investigated observers' impressions of the severity of online abuse on Twitter, the blame attributed to celebrities for the abuse they received, and the role of the dark triad of observers' personality factors (Machiavellianism, narcissism, and psychopathy) in these decisions. We manipulated celebrity tweet content (negative, neutral, positive) and the volume of abusive comments (high, low) the tweets received. Celebrities received more blame the more negative their initial tweet was, and incidents were perceived as least severe following a negative tweet with a high volume of abuse. Observer impressions were influenced by their dark triad personality factors. Following negative tweets, as observer narcissism increased, victim blame increased and perceived severity decreased. Following positive tweets, as observer psychopathy increased, perceived severity decreased. Results are discussed in the context of the Warranting Theory of online impression formation and the ramifications for celebrity social media use are explored

User-Centered Design of A Novel Risk Prediction Behavior Change Tool Augmented With an Artificial Intelligence Engine (MyDiabetesIQ):A Sociotechnical Systems Approach

BACKGROUND: Diabetes and its complications account for 10% of annual health care spending in the United Kingdom. Digital health care interventions (DHIs) can provide scalable care, fostering diabetes self-management and reducing the risk of complications. Tailorability (providing personalized interventions) and usability are key to DHI engagement/effectiveness. User-centered design of DHIs (aligning features to end users’ needs) can generate more usable interventions, avoiding unintended consequences and improving user engagement. OBJECTIVE: MyDiabetesIQ (MDIQ) is an artificial intelligence engine intended to predict users’ diabetes complications risk. It will underpin a user interface in which users will alter lifestyle parameters to see the impact on their future risks. MDIQ will link to an existing DHI, My Diabetes My Way (MDMW). We describe the user-centered design of the user interface of MDIQ as informed by human factors engineering. METHODS: Current users of MDMW were invited to take part in focus groups to gather their insights about users being shown their likelihood of developing diabetes-related complications and any risks they perceived from using MDIQ. Findings from focus groups informed the development of a prototype MDIQ interface, which was then user-tested through the “think aloud” method, in which users speak aloud about their thoughts/impressions while performing prescribed tasks. Focus group and think aloud transcripts were analyzed thematically, using a combination of inductive and deductive analysis. For think aloud data, a sociotechnical model was used as a framework for thematic analysis. RESULTS: Focus group participants (n=8) felt that some users could become anxious when shown their future complications risks. They highlighted the importance of easy navigation, jargon avoidance, and the use of positive/encouraging language. User testing of the prototype site through think aloud sessions (n=7) highlighted several usability issues. Issues included confusing visual cues and confusion over whether user-updated information fed back to health care teams. Some issues could be compounded for users with limited digital skills. Results from the focus groups and think aloud workshops were used in the development of a live MDIQ platform. CONCLUSIONS: Acting on the input of end users at each iterative stage of a digital tool’s development can help to prioritize users throughout the design process, ensuring the alignment of DHI features with user needs. The use of the sociotechnical framework encouraged the consideration of interactions between different sociotechnical dimensions in finding solutions to issues, for example, avoiding the exclusion of users with limited digital skills. Based on user feedback, the tool could scaffold good goal setting, allowing users to balance their palatable future complications risk against acceptable lifestyle changes. Optimal control of diabetes relies heavily on self-management. Tools such as MDMW/ MDIQ can offer personalized support for self-management alongside access to users’ electronic health records, potentially helping to delay or reduce long-term complications, thereby providing significant reductions in health care costs

Early social complexity at Bolas, Costa Rica: First year southern Costa Rica archaeological project (Scrap) results

El Proyecto Arqueológico del Sur de Costa Rica (SCRAP) investiga los contextos del desarrollo de desigualdad social en el sitio Bolas, un sitio socioceremonial en el sur de Costa Rica. La producción de artesanías y actividades ceremoniales son los principales temas de investigación. A diferencia de Barriles en Panamá, un sitio similar, los indicadores domésticos de jerarquía no son claros. Los resultados del primer año demuestran que el asentamiento de Bolas es más grande que lo reportado, y contiene múltiple sitios con montículos con evidencias de la realización de diferentes actividades en cada uno.The Southern Costa Rica Archaeological Project (SCRAP) investigates the contexts for the development of social inequality at the socioceremonial site of Bolas in southern Costa Rica. Craft production and ceremonial activities are the main interests of the project. Unlike Barriles in Panama, a similar site, domestic indicators of high status were elusive. The first year results demonstrate that the Bolas complex is much larger than originally reported, composed of multiple mounded sites with different activities occurring in each one of them.

Initial tweet valence, abuse volume, and observer Dark Tetrad characteristics influence perceptions of female celeb

Research into relationships between victim-generated content, abuse received, and observer characteristics when considering Twitter abuse has been limited to male victims. We evaluated participant perceptions of female celebrity victims and abuse received on Twitter. We used a 3 (Initial Tweet Valence; negative, neutral, positive) × 2 (Abuse Volume; low, high) repeated measures design and online survey method. Participants were shown tweets generated by six female celebrities, counterbalanced such that each participant saw each celebrity in one Valence-Volume condition. Stimuli were presented across six ‘lists’ such that celebrity ‘victims’ could be rotated across Valence-Volume pairings. Participants rated—per target stimulus—the level of blame attributable to the victim and the perceived severity of the incident. Furthermore, participants were asked to complete a Dark Tetrad scale—measuring their Machiavellianism, Narcissism, Psychopathy, and Sadism. Analyses determined that victim-blaming was influenced by victim Initial Tweet Valence (greater victim-blaming associated with more-negative content) and observer Machiavellianism. Perceived severity was influenced by victim Initial Tweet Valence, Volume of Abuse received, and observer Machiavellianism. Results were consistent with previous research involving male celebrity victims. Further research is needed to understand the contributions of participants’ hostile and benevolent sexism, as well as the role of victim attractiveness