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11 – 20 of 82Nigel L. Williams, Nicole Ferdinand and John Bustard
Advances in artificial intelligence (AI) natural language processing may see the emergence of algorithmic word of mouth (aWOM), content created and shared by automated tools. As…
Abstract
Purpose
Advances in artificial intelligence (AI) natural language processing may see the emergence of algorithmic word of mouth (aWOM), content created and shared by automated tools. As AI tools improve, aWOM will increase in volume and sophistication, displacing eWOM as an influence on customer decision-making. The purpose of this paper is to provide an overview of the socio technological trends that have encouraged the evolution of informal infulence strategies from WOM to aWOM.
Design/methodology/approach
This paper examines the origins and path of development of influential customer communications from word of mouth (WOM) to electronic word of mouth (eWOM) and the emerging trend of aWOM. The growth of aWOM is theorized as a result of new developments in AI natural language processing tools along with autonomous distribution systems in the form of software robots and virtual assistants.
Findings
aWOM may become a dominant source of information for tourists, as it can support multimodal delivery of useful contextual information. Individuals, organizations and social media platforms will have to ensure that aWOM is developed and deployed responsibly and ethically.
Practical implications
aWOM may emerge as the dominant source of information for tourist decision-making, displacing WOM or eWOM. aWOM may also impact online opinion leaders, as they may be challenged by algorithmically generated content. aWOM tools may also generate content using sensors on personal devices, creating privacy and information security concerns if users did not give permission for such activities.
Originality/value
This paper is the first to theorize the emergence of aWOM as autonomous AI communication within the framework of unpaid influence or WOM. As customer engagement will increasingly occur in algorithmic environments that comprise person–machine interactions, aWOM will influence future tourism research and practice.
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Dipanjan Goswami, Sakun Boon-Itt, Neera Jain and D.R. Agarwal
The quality and reliability of medical communication for branded drug adoption is extremely critical, not only for safeguarding patient interests but also for ensuring successful…
Abstract
Purpose
The quality and reliability of medical communication for branded drug adoption is extremely critical, not only for safeguarding patient interests but also for ensuring successful investments by multinational pharmaceutical firms. This paper predicts doctors’ prescribing intentions based on communication relationship among factors for late entrant branded drugs, compared with pioneering brand choice, for treating chronic diseases such as hypertension.
Design/methodology/approach
The constructs were validated with structural equation model for a sample set of 151 doctors from private hospitals in the National Capital Region of India.
Findings
This research reveals communication drivers and draws on theory to suggest that the doctor’s behavioural prescription intentions, subject to social influence from their colleagues, leads to lower adoption responses.
Research limitations/implications
Given that limitations on sample size are often unavoidable, this study reveals that, due to the availability of substituting brands, alternate therapeutic routes and lack of availability of a practical guide for prescription, a communication model needs to be developed and validated.
Practical implications
Furthermore, managers of pharmaceutical firms should differentiate between the effects of direct and indirect communication–integration efforts for minimizing uncertainty in drug adoption in the context of the fragmented and unpredictable Indian market.
Originality/value
A late entrant may lose its dominant market share to alternate brands from other suppliers due to communication gaps in an unstructured market, leading to low adoption intentions. The study provides business theorists, drug marketers and health-care professionals with unique insights into specific communication drivers of prescribing decisions, aimed at ensuring reliable and appropriate drug adoption in Indian markets.
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Jonas Nilsson and Jeanette Carlsson Hauff
Students in the marketing discipline have been reported to struggle with quantitative methods. This paper aims to focus on whether it is possible to increase student confidence…
Abstract
Purpose
Students in the marketing discipline have been reported to struggle with quantitative methods. This paper aims to focus on whether it is possible to increase student confidence and reduce anxiety with quantitative data analysis even when limited teaching resources are available. It reports on two half-day initiatives to teach quantitative methods that followed the principles of integration of method into a substantive course (as opposed to stand-alone course) and hands-on approach (as opposed to using a theoretical and hands-off approach).
Design/methodology/approach
Over the course of three semesters, 92 students that took part of the sessions answered a survey where they reported their basic understanding, confidence, practical abilities and anxiety with quantitative methods.
Findings
The results indicate significant improvements in self-reported basic understanding, confidence, practical abilities and anxiety. Further analysis indicated that neither gender nor previous statistical background had an impact on perceived benefit with the initiative.
Practical implications
In all, the study indicates that integration and hands-on approaches may be beneficial to reduce anxiety and increase confidence with quantitative data analysis, even when this initiative is limited in time and resources.
Originality/value
The study presents an approach to reducing anxiety and increasing confidence with quantitative data analysis. Teaching initiatives like this may be beneficial in situations when students experience high levels of statistics anxiety.
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Nikunj Kumar Jain, Alok Kumar Singh and Kapil Kaushik
The purpose of this paper is to analyse service quality in the automobile maintenance and repair industry. A conceptual structural model is developed to investigate the impact of…
Abstract
Purpose
The purpose of this paper is to analyse service quality in the automobile maintenance and repair industry. A conceptual structural model is developed to investigate the impact of service quality, perceived service fairness and convenience on customer service satisfaction. The impact of service satisfaction and brand trust on word of mouth (WOM) is also explored, and the study assesses the mediating effect of customer service satisfaction on the relationship between service quality and WOM.
Design/methodology/approach
Data from a questionnaire-based survey of 259 users of automobile maintenance and repair centres were analysed using covariance-based structural equation modelling.
Findings
The findings indicate that service quality dimensions (reliability, responsiveness and empathy), perceived service fairness and convenience are positively associated with customer service satisfaction, and that service satisfaction and trust positively influence WOM. The findings support the mediating effect of service satisfaction on the relationship between reliability and responsiveness and WOM.
Research limitations/implications
The study’s main limitation is the cross-sectional design, which limits the generalisability of the findings.
Practical implications
To ensure customer satisfaction and generate trust and WOM, automobile maintenance and repair service centres should improve reliability, responsiveness and empathy, as well as perceived service fairness and convenience.
Originality/value
The study demonstrates that the reliability and responsiveness dimensions of service quality are the most significant predictors of customer service satisfaction in the automobile maintenance and repair industry.
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Chiara Orsingher and Jochen Wirtz
Empirical research presents conflicting findings with regards to the effectiveness of referral reward programs (RRPs) and supports two alternative and conflicting views on the…
Abstract
Purpose
Empirical research presents conflicting findings with regards to the effectiveness of referral reward programs (RRPs) and supports two alternative and conflicting views on the effectiveness of incentivizing recommendations. They are, first, a positive effect via perceived attractiveness of the incentive, and second, a negative effect via metaperception of the recommendation. The purpose of this paper is to examine these two opposing psychological mechanisms to reconcile the conflicting findings.
Design/methodology/approach
The authors conducted three experiments. Study 1 tests the base model. Studies 2 and 3 add moderators to test whether each mediating variable operates exclusively on its intended relationship.
Findings
Incentive size enhanced the attractiveness of an incentive, but reduced the metaperception favorability of the recommendation. These two opposing mechanisms operated in parallel, independently and fully mediated the effects of incentive size to likelihood of making a recommendation. Thus, the net impact of incentives on recommendation behavior depended on the relative strengths of these two opposing forces.
Practical implications
The study recommends managers to design RRPs with incentives that recommenders perceive as highly useful (i.e. to increase attractiveness) but have a low face value (i.e. to reduce metaperception concerns) and to target RRPs to strong rather than weak ties.
Originality/value
Our work offers an integrated theoretical account of consumers’ responses to incentivized recommendations and provides managerially relevant guidelines for the design of effective RRPs.
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Dora E. Bock, Jeremy S. Wolter and O.C. Ferrell
Artificial intelligence (AI) is currently having a dramatic impact on marketing. Future manifestations of AI are expected to bring even greater change, possibly ushering in the…
Abstract
Purpose
Artificial intelligence (AI) is currently having a dramatic impact on marketing. Future manifestations of AI are expected to bring even greater change, possibly ushering in the realization of the fourth industrial revolution. In accord with such expectations, this paper aims to examine AI’s current and potential impact on prominent service theories as related to the service encounter.
Design/methodology/approach
This paper reviews dominant service theories and their relevance to AI within the service encounter.
Findings
In doing so, this paper presents an integrated definition of service AI and identifies the theoretical upheaval it creates, triggering a plethora of key research opportunities.
Originality/value
Although scholars and practitioners are gaining a deeper understanding of AI and its role in services, this paper highlights that much is left to be explored. Therefore, service AI may require substantial modifications to existing theories or entirely new theories.
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Henrich R. Greve and Seo Yeon Song
Industry platforms can alter relations among exchange partners in such a way that the industry structure is changed. The focus of much industry platform research has been on how…
Abstract
Industry platforms can alter relations among exchange partners in such a way that the industry structure is changed. The focus of much industry platform research has been on how platform creation and leadership offers advantages to the most central firms, but platforms can also be advantageous for small specialist firms that compete with the most central firms. We examine book publishing as an example of an industry in which the central players – large publishing firms – are losing power to self-publishing authors because the distributor Amazon has a powerful platform for customers to communicate independently, and the non-publishing platform Twitter also serves as a medium for readers to discuss and review books. Our empirical analysis is based on downloaded sales statistics for Amazon Ebooks, matched with Amazon reviews of the same books and tweets that refer to the book or the author. We analyze how Ebook sales are a function of publisher, Amazon reviews, and tweets, and we are able to assess the importance of each factor in the sale of book titles. The main finding is that Amazon reviews are powerful drivers of book sales, and have greater effect on the sales of books that are not backed by publishers. Twitter also affects book sales, but less strongly than Amazon reviews.
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Sandy Jeanquart Miles and Glynn Mangold
The focus of this paper was twofold: to examine critical team leader behaviors (as perceived by the subordinate) that result in team member satisfaction; and to determine if there…
Abstract
The focus of this paper was twofold: to examine critical team leader behaviors (as perceived by the subordinate) that result in team member satisfaction; and to determine if there is a significant difference between the perceptions of team leaders and team members regarding the level of team satisfaction and factors that predict team leader performance. Results indicate that team member satisfaction was influenced by: the extent to which communication within the group was open; and the team leaders’ performance. Team leader performance was influenced by the team members’ satisfaction with their leaders’ ability to resolve conflicts and the teams’ openness in communication. Team members’ and leaders’ perceptions did not differ significantly regarding open communication in the group, however, team members assessed their leaders’ performance less favorably than the team leaders assessed themselves and were less satisfied with the team leaders’ ability to resolve conflicts.
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Satish Sasalu Maheswarappa, Bharadhwaj Sivakumaran and Arun G. Kumar
The purpose of this paper is to investigate returns to search (getting a better product and/or a lower price as a result of search) when consumers use/do not use recommendation…
Abstract
Purpose
The purpose of this paper is to investigate returns to search (getting a better product and/or a lower price as a result of search) when consumers use/do not use recommendation agents (RAs). Specifically, it studies the effect of RAs/no RAs on decision quality, decision confidence and decision satisfaction taking into account subjective knowledge (SK) and involvement.
Design/methodology/approach
This paper employed two between-subjects factorial experimental designs with subjects searching for digital cameras in a simulated online digital camera store. The experiment was conducted with graduate students in Chennai, Bengaluru and Mysore in India.
Findings
Results of two online experiments showed that when consumers used RAs, low search led to better decision quality, whereas when consumers did not use RAs, medium search led to optimum decision quality. When consumers use RAs, SK had a U-shaped influence on the decision quality indicating that decision quality was the lowest for those with medium SK. When consumers did not use RAs, the effect of SK on decision quality was an inverted U-shape, indicating optimum decision quality for medium SK consumers. When consumers did not use RAs, subjects with high involvement made better choices, whereas when consumers used RAs, low involvement subjects made better choices. However, subjects who searched more had higher decision confidence and decision satisfaction even if their choices were not better.
Originality/value
The effect of RA vs no RA in conjunction with relevant consumer characteristics influencing decision quality of the consumer is demonstrated in this study. The findings have important managerial, consumer and theoretical contributions to make.
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This study aims to explore the importance of past behaviour and financial literacy in the investment decision-making of individual investors and examines the validity of the…
Abstract
Purpose
This study aims to explore the importance of past behaviour and financial literacy in the investment decision-making of individual investors and examines the validity of the theory of planned behaviour in this context.
Design/methodology/approach
The study used a self-administered questionnaire and adopted the convenience sampling technique followed by a snowball sampling method for the survey to collect data from the individual investors covering the four distinct states of India. Collected data were analysed on AMOS 20.0 using two-step structural equation modelling (SEM).
Findings
Results indicated a significant effect of all the predictive variables. Past behaviour showed no significant direct impact on investor's intention; however, it had an indirect significant relationship while mediated by the attitude of investors. The multiple squared correlation (R2) showed that the final model could explain 36% of the variance in investors' intention towards stock investment which signified a successful implementation of the TPB model along with external variables added to it. Moreover, Indian investors were found to be highly influenced, primarily, by social pressure which could be curbed through financial literacy.
Practical implications
A significant importance of subjective norms was found on stock market participation which could be a strategic theme for the government and the policymakers to educate investors through their opinion leaders for increasing their participation. Moreover, by doing so investors could control their behaviour and take rational decisions.
Originality/value
This study extended the understandings of investor's decision-making behaviour using TPB by incorporating the two external variables viz., Financial literacy and past behaviour. The addition of past behaviour is perhaps the novelty of this article since such examination has not been conducted empirically especially in the case of developing countries like India.
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