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The study aims to provide insights in the sensemaking process and the use of business analytics (BA) for project selection and prioritisation in start-up settings. A major focus is on the various ways start-ups can understand their data through the analytical process of sensemaking.

This is a comparative case study of two start-ups that use BA in their projects. The authors follow an interpretive approach and draw from the constructivist grounded theory method (GTM) for the purpose of data analysis, whereby the theory of sensemaking functions as the sensitising device that supports the interpretation of the data.

The key findings lie within the scope of project selection and prioritisation, where the sensemaking process is implicitly influenced by each start-up's strategy and business model. BA helps start-ups notice changes within their internal and external environment and focus their attention on the more critical questions along the lines of their processes, operations and business model. However, BA alone cannot support decision-making around less structured problems such as project selection and prioritisation, where intuitive judgement and personal opinion are still heavily used.

This study extends the research on BA applied in organisations as tools for business development. Specifically, the authors draw on the literature of BA tools in support of project management from multiple perspectives. The perspectives include but are not limited to project assessment and prioritisation. The authors view the decision-making process and the path from insight to value, as a sensemaking process, where data become part of the sensemaking roadmap and BA helps start-ups navigate the decision-making process.

This paper investigates the strategic behavior of algorithmic trading firms from an innovation economics perspective. The authors seek to uncover the sources of competitive advantage these firms develop to make markets inefficient for them and enable their survival.

First, the authors review expected capability, a quantitative behavioral model of the sustainable, or reliable, profits that lead to survival. Second, they present qualitative data gathered from semi-structured interviews with industry professionals as well as from the academic and industry literatures. They categorize this data into first-order concepts and themes of opportunity-, advantage- and meta-seeking behaviors. Associating the observed sources of competitive advantages with the components of the expected capability model allows us to describe the economic rationale these firms have for developing those sources and explain how they survive.

The data reveals ten sources of competitive advantages, which the authors label according to known ones in the strategic management literature. We find that, due to the dynamically complex environments and their bounded resources, these firms seek heuristic compromise among these ten, which leads to satisficing. Their application of innovation methodology that prescribes iterative ex post hypothesis testing appears to quell internal conflict among groups and promote organizational survival. The authors believe their results shed light on the behavior and motivations of algorithmic market actors, but also of innovative firms more generally.

Based upon their review of the literature, this is the first paper to provide such a complete explanation of the strategic behavior of algorithmic trading firms.

Being acquainted with both lean and action learning in theory and in practice, this study finds that the theoretical complementarity of these two research streams has traditionally been underexploited. In this conceptual paper, this study aims to advance the theoretical understanding of lean by exploring the complementarity of lean thinking and action learning leading to a proposed integrated theory of these two research streams. Target audience is the operations management research community.

By deliberately adopting a process of theorising, this paper explores, reflects upon and combines individual experiences of researching, teaching and engaging in lean and action learning as operations management scholars.

Having taken a gemba walk through the literature and practices of lean and action learning, this study views and notices a systematic and complementary relationship between the two domains. The overlapping theoretical and practical complementarities of lean and action learning suggest that these two research streams are ripe for synthesis into an integrated theory. This finding provides an opportunity to (1) progress towards an integrative design of interventions leading to more sustainable lean system adoptions and (2) add new depth to our theoretical explanation of the success and failures of lean system adoptions.

This paper contributes an original integrated theory perspective on lean and action learning.

This study aims to develop a unified theoretical framework that presents a cohesive picture of workplace cyberbullying to better understand the interplay between cyberbullying, its effects on organizations and organizational controls enacted to contain these effects.

The study conducts a theoretical review of the workplace cyberbullying literature between 2005 and 2021 drawing upon existing literature and two important theories, the routine activities theory and control theory. The final sample of 54 empirical papers represents a comprehensive body of literature on cyberbullying published across various disciplines.

A theoretical model of workplace cyberbullying is developed, which highlights major antecedents to workplace cyberbullying and its impact on individual employees as well as organizations.

As firms increasingly rely on information and communication technologies (ICTs), the misuse of ICTs in the form of cyberbullying is also increasing. Workplace cyberbullying severely hurts an organization’s employees and compromises the efficacy of its information systems. Fortunately, various controls can be utilized by firms to minimize workplace cyberbullying and its attendant costs. In all, eleven propositions are offered, providing a robust agenda for future research. The authors also offer insights for practitioners on how to minimize cyberbullying in the workplace and its damaging effects.

The purpose of this paper is to scrutinise the effectiveness of four derivative exchanges’ enforcement efforts since 2007. These exchanges include the Commodity Exchange Inc. and ICE Futures US from the United States and ICE Futures Europe and the London Metal Exchange from the UK.

The paper examines 799 enforcement notices published by four exchanges through a behavioural science lens: HUMANS conceived by Hunt (2023) in Humanizing Rules: Bringing Behavioural Science to Ethics and Compliance.

The paper finds the effectiveness of the exchanges’ enforcement efforts to be a mixed picture as financial markets transition from the digital to artificial intelligence era. Humans remain a key cog in the wheel of market participants’ trading operations, albeit their roles have changed. Despite this, some elements of exchanges’ enforcement regimes have not kept pace with the move from floor to remote trading. However, in other respects, their efforts are or should be, effective, at least in behavioural terms.

The paper’s findings are arguably limited to exchanges based in Anglophone jurisdictions. The information published by the exchanges is variable, making “like-for-like” comparisons difficult in some areas.

The paper makes several recommendations that, if adopted, could help exchanges to increase the potency of their enforcement programmes.

A key aim of the paper is to shift the lens through which the debate concerning the efficacy of exchange-level oversight is conducted. Hitherto, a legal lens has been used, whereas this paper uses a behavioural lens.

This study aims to examine the impact of perceived risk dimensions, confirmation, perceived usefulness and perceived ease of use on user satisfaction and their continuance intention to use mobile payments across Vietnam based on the extended technology continuance theory (TCT).

This study used an online questionnaire-based survey design to collect data from 417 respondents using judgmental and snowball sampling techniques. The respondents in this survey are personal users of mobile payments across Vietnam. Data analyses and hypothesis testing were carried out using the partial least squares structural equation modeling.

The findings demonstrate that physical risk, time loss risk, opportunity cost risk, confirmation, perceived ease of use and perceived usefulness are important elements influencing consumers’ satisfaction toward continuance intentions to use mobile payment services. Satisfaction is also significantly associated with continuance intentions to use mobile payments across Vietnam. Other relationships, including functional risk, social risk, financial risk and information risk are not significantly related to satisfaction. These results are expected to be useful for mobile payment service providers. Understanding the factors mentioned in this study enables mobile payment service providers to improve their offerings strategically and then motivate their clients to keep using mobile payments.

The work is among the very few bodies of empirical research to investigate the continuance intention to use mobile payments using the extended TCT by incorporating the various dimensions of perceived risk construct in the fintech sector to develop a research model for this study. Furthermore, combining with perceived risk dimensions, this study expands the TCT model’s mobile app to the fintech sector, and advances the understanding of the use of the extended TCT in the fintech sector and adds to the theory.

AI-driven product recommendation chatbots have markedly reduced operating costs and increased sales for marketers. However, previous literature has paid little attention to the effects of the personality of e-commerce chatbots. This study aimed to examine the ways that the interplay between the chatbot's and the user's personality can increase favorable product attitudes and future intentions to use the chatbot. Based on prior literature, we specifically focused on the degree of extroversion of both chatbot and user.

A total of 291 individuals participated in this study. Two different versions of chatbot were created for this study (i.e. extroversion: high vs. low). Participants self-reported their degree of extroversion. The PROCESS macro Model 1 and Model 7 with the Johnson–Neyman technique were employed to test the hypotheses.

The results showed that the high extroversion chatbot elicited greater user satisfactions and perceptions of chatbot friendliness among users with a high level of extroversion. On the contrary, the low extroversion chatbot resulted in greater user satisfactions and perceived chatbot friendliness among users with a low level of extroversion. This study further found that user satisfactions and perceived chatbot friendliness mediated the effects of the chatbot on greater intentions to use the chatbot and more favorable product attitudes.

By showing the effects of matching the personality of the chatbot and user, this study revealed that similarity-attraction effects also apply to human–chatbot interaction in e-commerce. Future studies would benefit by investigating the similarity-attraction effects in different characteristics, such as appearance, opinion and preference. This study also provides useful information for e-commerce marketers and chatbot UX/UI designers.

This study explores the differences between digital immigrants (DIs) and digital natives (DNs) in the continuance of routine and innovative information system use.

A quantitative survey was conducted with two different samples comprising 100 DIs and 152 DNs in mandatory information system use contexts. Data were analyzed with structural equation modeling to examine the hypothesized relationships in the research model.

Results revealed differences among digital nativity groups. The effect of confirmation of expectations about system use on satisfaction is stronger for DNs whereas the effect on task–technology fit (TTF) is similar in both digital groups. Interestingly, significant differences between digital nativity groups occur in routine use. For DIs, TTF and habit are significant while for DNs, satisfaction significantly affects routine use. The results show no difference between digital native groups regarding innovative use.

This study extends the concept of digital nativity to routine and innovative system use, contributing to an enhanced understanding about the differences in information systems continuance (ISC) based on digital nativity. It also provides a fine-grained discussion of how to classify digital nativity and its impact in working contexts and extends the IS continuance model by considering two types of IS usage.

Based on resource-based and dynamic capabilities theorizing, this study explores how human resource analytics (HRA) can improve human resource management (HRM) performance and organizational performance, with creative problem-solving capability (CPSC) as an underlying mediator for creating value from HRA. It also explores how data quality and HRA personnel expertise act as moderators in this relationship.

Hypotheses are tested in an empirical study including 191 firms using partial least square structural equation modeling technique.

The findings confirm the direct and indirect effect of HRA use and maturity on HRM and organizational performance, as well as the mediating role of CPSC. HRA personnel expertise was found to moderate the relationship between HRA and CPSC, data quality being an important factor.

The findings contribute to the sparse evidence of value creation from HRA use/maturity on HRM and organizational outcomes, providing a theoretical logic of resource-based view and dynamic capabilities view based on the underlying causal mechanism through which HRA creates value. The study identified complementary capabilities which when combined with HRA use/maturity and CPSC result in value creation.

The aim of this study is to examine the role of relational benefits and brand experience measurements on willingness to pay more (WPM), effects of word of mouth (WOM) and repurchase intention (RI) in fast-food restaurants (FFR).

Employing an online questionnaire survey with a sample size of 503 respondents, the quantitative methodology included multiple regression and factor analysis to facilitate the analyses of data.

Relational benefits and their dimensions (confidence, special treatment and social benefits) found to positively impact WPM, WOM and RI. With reference to brand experiences, the current study found that behavioural and intellectual experiences have significant and positive effects on WPM, WOM and RI. Surprisingly, no positive significance was identified between sensory experiences and WPM, WOM and RI.

The findings show that relational benefits and brand experience dimensions play an essential role in improving brand loyalty.

The current study subscribes to the concept of relationship marketing theory, suggesting that loyalty to FFRs can be enhanced by offering customers relational benefits and augmenting their brand experiences.