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This study, a theoretical article, aims to introduce new institutionalism as a framework through which business and management researchers can explore the significance of artificial intelligence (AI) in organizations. Although the new institutional theory is a fully established research program, the neo-institutional literature on AI is almost non-existent. There is, therefore, a need to develop a deeper understanding of AI as both the product of institutional forces and as an institutional force in its own right.

The authors follow the top-down approach. Accordingly, the authors first briefly describe the new institutionalism, trace its historical development and introduce its fundamental concepts: institutional legitimacy, environment and isomorphism. Then, the authors use those as the basis for the queries to perform a scoping review on the institutional role of AI in organizations.

The findings reveal that a comprehensive theory on AI is largely absent from business and management literature. The new institutionalism is only one of many possible theoretical perspectives (both contextually novel and insightful) from which researchers can study AI in organizational settings.

The authors use the insights from new institutionalism to illustrate how a particular social theory can fit into the larger theoretical framework for AI in organizations. The authors also formulate four broad research questions to guide researchers interested in studying the institutional significance of AI. Finally, the authors include a section providing concrete examples of how to study AI-related institutional dynamics in business and management.

Given the critical role of user-generated content (UGC) in e-commerce, exploring various aspects of UGC can aid in understanding user purchase intention and commodity recommendation. Therefore, this study investigates the impact of UGC on purchase decisions and proposes new recommendation models based on sentiment analysis, which are verified in Douban, one of the most popular UGC websites in China.

After verifying the relationship between various factors and product sales, this study proposes two models, collaborative filtering recommendation model based on sentiment (SCF) and hidden factors topics recommendation model based on sentiment (SHFT), by combining traditional collaborative filtering model (CF) and hidden factors topics model (HFT) with sentiment analysis.

The results indicate that sentiment significantly influences purchase intention. Furthermore, the proposed sentiment-based recommendation models outperform traditional CF and HFT in terms of mean absolute error (MAE) and root mean square error (RMSE). Moreover, the two models yield different outcomes for various product categories, providing actionable insights for organizers to implement more precise recommendation strategies.

The findings of this study advocate the incorporation of UGC sentimental factors into websites to heighten recommendation accuracy. Additionally, different recommendation strategies can be employed for different products types.

This study introduces a novel perspective to the recommendation algorithm field. It not only validates the impact of UGC sentiment on purchase intention but also evaluates the proposed models with real-world data. The study provides valuable insights for managerial decision-making aimed at enhancing recommendation systems.

The existing collaborative filtering algorithm may select an insufficiently representative customer as the neighbor of a target customer, which means that the performance in providing recommendations is not sufficiently accurate. This study aims to investigate the impact on recommendation performance of selecting influential and representative customers.

Some studies have shown that review helpfulness and consistency significantly affect purchase decision-making. Thus, this study focuses on customers who have written helpful and consistent reviews to select influential and representative neighbors. To achieve the purpose of this study, the authors apply a text-mining approach to analyze review helpfulness and consistency. In addition, they evaluate the performance of the proposed methodology using several real-world Amazon review data sets for experimental utility and reliability.

This study is the first to propose a methodology to investigate the effect of review consistency and helpfulness on recommendation performance. The experimental results confirmed that the recommendation performance was excellent when a neighbor was selected who wrote consistent or helpful reviews more than when neighbors were selected for all customers.

This study investigates the effect of review consistency and helpfulness on recommendation performance. Online review can enhance recommendation performance because it reflects the purchasing behavior of customers who consider reviews when purchasing items. The experimental results indicate that review helpfulness and consistency can enhance the performance of personalized recommendation services, increase customer satisfaction and increase confidence in a company.

This chapter focuses on women's descriptions of their own violence in nineteenth-century Ireland, as revealed in prisoner petitions held in the National Archives of Ireland. It uses the case files of women imprisoned or sentenced to death for violent crimes such as infanticide, manslaughter, murder, wounding and assault. This chapter takes an empirical approach and considers the ways that women explained and rationalised their violent acts. An analysis of the petitions offers an insight into women's views of their own violence, gendered attitudes at the time, and women's sense of the factors that might lead to a commutation of sentence. The accuracy or truthfulness of the petitions is not important in this study; instead, the chapter explores the self-image that women wanted to portray and the tactics that they opted to use to seek a reduction in their sentences. As shown in this chapter, most women emphasised their passivity: they typically claimed to be innocent, coerced or provoked into violence.

The accelerating past globalisation had pressurised various types of enterprises, including state-owned enterprises (SOEs), to adopt appropriate decision-making approaches for their internationalisation strategies. The present book chapter illustrates the role that an entrepreneurial approach played in the decision-making process about the international expansion of an incumbent and large, SOE after its initial internationalisation. The case of a formerly state-owned telecommunication enterprise from Scandinavia will be explored that highlights aspects of entrepreneurial decision-making, internal organisational changes, and the influence of individual managers within the executive management team which influenced the process of internal decision-making. The empirical chapter makes important contributions to notably the practice of entrepreneurial decision-making for internationalisation; it unveils the complexities of internal decision-making processes, including the struggles between individual managers, and thereby provides a better understanding for management practitioners about decision-making for competitiveness and growth during the internationalisation of large, yet inexperienced enterprises.

This paper aims to investigate a condition under which identity salience effects are weakened. By examining how identity salience influences individuals’ product judgment in a domain of trade-offs, the current research demonstrates that the utilitarian value of a product is an important determinant of the effectiveness of identity salience on product judgment.

This research consists of two experiments. In Experiment 1, the authors examined whether identity salience effects were mitigated when the level of the perceived utilitarian value of an identity-incongruent product was greater than that of an identity-congruent product. In Experiment 2, the authors examined the effectiveness of internal attribution as a moderator that strengthens identity salience effects when the perceived utilitarian value of an identity-incongruent (vs. identity-congruent) product is higher.

In Experiment 1, the authors show that when the utilitarian value of a product with an attribute congruent (vs. incongruent) with one’s salient identity is lower, individuals do not show a greater preference for the identity-congruent (vs. identity-incongruent) product, mitigating the identity salience effects. Experiment 2 demonstrates that when individuals with a salient identity attribute a decision outcome to the self, they display a greater preference for the identity-congruent product even when its utilitarian value is lower compared to that of the identity-incongruent product.

The research contributes to previous research examining conditions under which identity salience effects are weakened [e.g. social influence by others (Bolton and Reed, 2004); self-affirmation (Cohen et al., 2007)] by exploring the role of the utilitarian value of a product, which has not been examined yet in prior research. Also, by doing so, the current research adds to the literature on identity salience in a domain of trade-offs (Benjamin et al., 2010; Shaddy et al., 2020, 2021). Finally, this research reveals that when a decision outcome is attributed to the self, identity salience effects become greater. By finding a novel determinant of identity salience effects (i.e. internal attribution), the present research contributes to the literature that has examined factors that amplify identity salience effects [e.g. cultural relevance (Chattaraman et al., 2009); social distinctiveness (Forehand et al., 2002); different types of groups (White and Dahl, 2007)].

The findings provide managerial insights on identity-based marketing by showing a condition under which identity-based marketing does not work [i.e. when the utilitarian value of an identity-congruent (vs. identity-incongruent) product is lower] and how to enhance the effectiveness of identity-based marketing by using internal attribution.

By exploring the role of utilitarian value, not yet examined in prior research, the present research adds to the knowledge of the conditions under which identity salience effects are weakened. Furthermore, by finding a novel determinant of identity salience effects (i.e. internal attribution), the research contributes to the literature on factors that amplify identity salience effects.

This paper aims to reveal the role of two theories that impact seniors’ entrepreneurial intentions. Both the socioemotional selectivity theory (SST) and the self-determination theory (SDT) re-shape seniors’ intentions to create entrepreneurial opportunities and activities after they retire.

This paper uses secondary data resources for developing the research concept, which might leverage seniors’ ultimate goal of creating entrepreneurial activities. A comprehensive past-paper analysis was performed. One hundred papers were initially considered for inclusion in this research. However, after a rigorous synthesisation process, 80 publications were selected for further analysis.

This paper presents an investigation of seniors’ entrepreneurship, with a specific emphasis on the SST and the SDT. It suggests potential models that could gauge senior entrepreneurs’ propensity to engage in entrepreneurial endeavours to support the socioeconomic advancement of society. Furthermore, this research discussed the limitations of the enlightening concepts presented to scholars and decision-makers.

The originality of this paper is illuminated by its idea of integrating two theories (the SST and the SDT), suggesting that these theories can possibly better observe senior entrepreneurs’ intentions in creating an entrepreneurial venture after they retire.

This paper aims to address the following issues: (1) most existing methods are based on recurrent network, which is time-consuming to train long sequences due to not allowing for full parallelism; (2) personalized preference generally are not considered reasonably; (3) existing methods rarely systematically studied how to efficiently utilize various auxiliary information (e.g. user ID and time stamp) in trajectory data and the spatiotemporal relations among nonconsecutive locations.

The authors propose a novel self-attention network–based model named SanMove to predict the next location via capturing the long- and short-term mobility patterns of users. Specifically, SanMove uses a self-attention module to capture each user's long-term preference, which can represent her personalized location preference. Meanwhile, the authors use a spatial-temporal guided noninvasive self-attention (STNOVA) module to exploit auxiliary information in the trajectory data to learn the user's short-term preference.

The authors evaluate SanMove on two real-world datasets. The experimental results demonstrate that SanMove is not only faster than the state-of-the-art recurrent neural network (RNN) based predict model but also outperforms the baselines for next location prediction.

The authors propose a self-attention-based sequential model named SanMove to predict the user's trajectory, which comprised long-term and short-term preference learning modules. SanMove allows full parallel processing of trajectories to improve processing efficiency. They propose an STNOVA module to capture the sequential transitions of current trajectories. Moreover, the self-attention module is used to process historical trajectory sequences in order to capture the personalized location preference of each user. The authors conduct extensive experiments on two check-in datasets. The experimental results demonstrate that the model has a fast training speed and excellent performance compared with the existing RNN-based methods for next location prediction.

This paper aims to tentatively explore the benefits of placing art’s knowledge-building tradition, with its capacity to disrupt and reframe, at the centre of how we look at alternative organizing and alternative economic spaces, positioning lived experience, its uncertainties intact, at the heart of researching and practicing social enterprise (SE).

The paper explores indeterminacy through two case-study narratives, one of an academic arts-based research project and the other of a unique organization it encountered.

The paper describes the way juxtaposition, encounter and drift value indeterminacy as central to generative processes, challenging the control central to management and its research.

The paper proposes that adopting an arts-based approach that challenges control can create a research instrument sensitive to similar tendencies in case studies, thus highlighting what is different and alternative about them. This responds to concerns about the diminishing centrality of SE’s democratizing ethic expressed in its scholarship, about creativity in its research and about its socially transformative potential.

The practice, by SEs of an approach welcoming chance, encounter, meandering paths and place-making with porous boundaries, proliferates transformative possibilities and is linked to democratization and participation.

Though dangerously challenging to accepted notions of academic rigour, this paper proposes an unusual thought experiment tied in with lived experiences, in themselves experimental in practice.

This study aims to explore and empirically examine an integrative model of the customer revenge process by linking two well-established theories of self-determination theory (SDT) and appraisal theory.

A survey of 901 respondents, followed by a post-hoc survey of 712 individuals, was conducted to examine the autonomous versus controlled orientations for revenge motivation.

The results show that customers’ orientation of motivation (OM) can regulate their revenge behavior (direct versus indirect) in case of service failures. Specifically, the interaction of OM components (i.e. autonomy, relatedness and competence) can play a significant role in the relationship between revenge predictors and revenge behavior. Implications for research and practice are discussed.

This paper offers a novel conceptual framework to explain the moderating effects of OM on the relationship between revenge predictors and revenge behavior. This study extends the application of SDT to the context of customer anger and revenge.