Andreas M. Kaplan and Michael Haenlein
The purpose of this paper is to provide a viewpoint on the historical roots and future evolution of social media.
Abstract
Purpose
The purpose of this paper is to provide a viewpoint on the historical roots and future evolution of social media.
Design/methodology/approach
This paper provides a summary of the authors' previous research and experience in the area of social media.
Findings
This paper contains practical insights on the consumer use and business potential of social media applications.
Originality/value
This viewpoint provides insights to anyone who is interested in researching consumer use of social media or using social media in a managerial context. It will be particularly helpful to business leaders who are looking for answers in the fast‐moving area of social media applications.
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Michael Haenlein and Andreas M. Kaplan
The management of unprofitable customer relationships and particularly their abandonment is a topic that has received increasing interest among practitioners and researchers over…
Abstract
Purpose
The management of unprofitable customer relationships and particularly their abandonment is a topic that has received increasing interest among practitioners and researchers over recent years. Within this manuscript, the authors aim to analyze the impact of unprofitable customer abandonment on the abandoning firm's current customers, specifically their exit, voice, and loyalty intentions toward the abandoning firm.
Design/methodology/approach
The study is based on an online experiment conducted among 385 US customers. Respondents were allocated randomly to one of ten conditions (five levels of tie strength x two types of abandonment strategy) and exposed to a scenario describing a customer abandonment decision implemented by a mobile phone provider. The resulting data were analyzed using a combination of analysis of variance (ANOVA) and structural equation modeling.
Findings
The study shows that current customers are significantly more likely to respond actively to unprofitable customer abandonment (exit/voice) than passively through silence and loyalty. Additionally, it shows that increasing satisfaction or switching cost among current customers are unlikely to limit the potential negative consequences of unprofitable customer abandonment. The only variable that drives the choice between exit, voice, and loyalty is the perceived attractiveness of the best alternative relationship.
Originality/value
This work analyzes for the first time how existing customers that the firm would like to retain react toward the news that the company proactively terminates unprofitable customer relationships. Therefore, insight is provided into the likely cost associated with unprofitable customer abandonment – a question that has not been the subject of any empirical study as of today.
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Yongfang Li, Si Shi, Yuliang Wu and Yang Chen
The purpose of this review is to systematically understand the development of enterprise social media (ESM) research, quantitatively analyze the landscape and track the…
Abstract
Purpose
The purpose of this review is to systematically understand the development of enterprise social media (ESM) research, quantitatively analyze the landscape and track the development of ESM literature and reveal new trends and challenges in ESM research.
Design/methodology/approach
Based on 321 relevant literature studies (2005–2020) collected from the Web of Science core collection, the visualization tool CiteSpace is used to conduct bibliometric cocitation and cooccurrence analyses to quantify and visualize the landscape and evolution of ESM research.
Findings
Through analyzing the author cocitation network, document cocitation network, journal cocitation network and keywords cooccurrence network, this review proposes an integrated research framework, which highlights major purposes, antecedents and consequences of ESM use in organizations and presents future research trends of ESM research.
Originality/value
Different from the existing qualitative review of ESM, this review adopts bibliometric review to quantify and visualize the landscape of ESM research.
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Alexandra L. Ferrentino, Meghan L. Maliga, Richard A. Bernardi and Susan M. Bosco
This research provides accounting-ethics authors and administrators with a benchmark for accounting-ethics research. While Bernardi and Bean (2010) considered publications in…
Abstract
This research provides accounting-ethics authors and administrators with a benchmark for accounting-ethics research. While Bernardi and Bean (2010) considered publications in business-ethics and accounting’s top-40 journals this study considers research in eight accounting-ethics and public-interest journals, as well as, 34 business-ethics journals. We analyzed the contents of our 42 journals for the 25-year period between 1991 through 2015. This research documents the continued growth (Bernardi & Bean, 2007) of accounting-ethics research in both accounting-ethics and business-ethics journals. We provide data on the top-10 ethics authors in each doctoral year group, the top-50 ethics authors over the most recent 10, 20, and 25 years, and a distribution among ethics scholars for these periods. For the 25-year timeframe, our data indicate that only 665 (274) of the 5,125 accounting PhDs/DBAs (13.0% and 5.4% respectively) in Canada and the United States had authored or co-authored one (more than one) ethics article.
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- Learn about ethical dilemmas in retailing with the advances in artificial intelligence (AI)
- Be able to reflect critically about the use and potential misuse of AI within the…
Abstract
Learning Outcomes
Learn about ethical dilemmas in retailing with the advances in artificial intelligence (AI)
Be able to reflect critically about the use and potential misuse of AI within the retailing industry
Learn about the history of AI
Be able to define and classify AI
Learn about ethical dilemmas in retailing with the advances in artificial intelligence (AI)
Be able to reflect critically about the use and potential misuse of AI within the retailing industry
Learn about the history of AI
Be able to define and classify AI