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Despite its flourishing development since first proposed, job crafting literature has provided limited insights into why people craft their jobs. This study theoretically develops a two-dimensional integrative framework for the motives of job crafting, including orientation (self-oriented vs work-oriented vs other-oriented) and self-determination (autonomous vs introjected vs external) dimensions. We further investigate the specific motives of job crafting from actor and observer perspectives.

We conducted two critical-incident recall surveys among 120 and 100 employees from varied sectors and organizations, who responded from the actor and observer perspective respectively. 395 and 299 valid open-ended responses were then collected and coded following the steps for content analysis.

Drawing from the proposed two-dimensional theoretical framework, we identified 16 specific job crafting motives from actor and observer perspectives.

Our findings remind managers to pay attention to employees' motives of job crafting and take appropriate managerial actions according to their varied motives.

By incorporating job crafting from the motivation literature and identifying diversified motives that drive employees to engage in job crafting, this qualitative study contributes to both the job crafting literature and the broader application of self-determination theory in the field of organizational behavior.

Although risk culture is a key determinant for an effective risk management, identifying the risk culture of a firm can be challenging due to the abstract concept of culture. This paper proposes a novel approach that uses unsupervised machine learning techniques to identify significant features needed to assess and differentiate between different forms of risk culture.

To convert the unstructured text in our sample of banks' 10K reports into structured data, a two-dimensional dictionary for text mining is built to capture risk culture characteristics and the bank's attitude towards the risk culture characteristics. A principal component analysis (PCA) reduction technique is applied to extract the significant features that define risk culture, before using a K-means unsupervised learning to cluster the reports into distinct risk culture groups.

The PCA identifies uncertainty, litigious and constraining sentiments among risk culture features to be significant in defining the risk culture of banks. Cluster analysis on the PCA factors proposes three distinct risk culture clusters: good, fair and poor. Consistent with regulatory expectations, a good or fair risk culture in banks is characterized by high profitability ratios, bank stability, lower default risk and good governance.

The relationship between culture and risk management can be difficult to study given that it is hard to measure culture from traditional data sources that are messy and diverse. This study offers a better understanding of risk culture using an unsupervised machine learning approach.

International trade and production have been increasingly organized around the configuration and evolution of global value chains (GVCs), even as the sustainable development goals (SDGs) have been established in an era of deepening globalization. The connection between these two processes raises some concerns around how economies, firms, and individuals can benefit from participation in the global economy. This chapter looks at the relationship between the relative positions of countries in high-tech GVCs and the impact on potential fulfillment of the SDGs. In this chapter, the authors make a first approach (descriptive analysis) to the relationship between the relative positions of countries in high-tech GVCs, possibilities for upgrading, and corresponding levels of inequality. The authors focus particularly on a set of indicators corresponding to Goal 1 (no poverty), Goal 5 (gender equality), Goal 9 (industry, innovation, and infrastructure), and Goal 10 (reduced inequalities). The findings reveal that the relationship between the position of a country in terms of forward and backward participations and the relative distance to fulfillment of the SDGs differs among distinct GVCs. While some patterns of income inequality reduction are observed in high-tech-related industries, gender inequality is not similarly affected. This confirms the relevance of building a two-dimensional framework that looks simultaneously at GVCs (i.e., the type of GVC and type of participation) as well as the distance from SDG achievement.

Logistics at work is rapidly changing. The changing trend is especially prominent when considering the active involvement of individuals that perform diverse forms of formal/informal “logistics work” (e.g. crowd logistics and self-collection). Thus, by conducting a synthesised review (n = 55), this study aims to provide a typology of individuals' logistics work.

The total social organisation of labour is used as a guiding framework. A deductive literature analysis is performed based on the identified journal articles.

The review findings reveal three major contexts where individuals perform logistics work: formal organisation, social community and private household, with a decreased level of formality. Under each context, individuals may be engaged in paid or unpaid activities, creating six forms of logistics work, termed as paid/voluntary professional logistics, incentivised/friendly social logistics and rewarded/free consumer logistics. Furthermore, an actor–sphere–resource–value conceptualisation of individual logistics is proposed, focussing on the chains of actors, work settings, resource input and value outcome.

The results provide a theoretical foundation for further research in individual- or consumer-centrism in logistics. Two research directions and seven research questions are presented for future investigation.

This paper aims to explore how service organizations can improve the effectiveness of well-being creation efforts given the pressing societal issues and global crises. In this paper, the authors examine two essential dimensions (dignity and vulnerability approach) to develop a theoretical framework. This framework can be used to increase the effectiveness of well-being outcomes created by transformative service initiatives (TSIs) and minimize their negative unintentional consequences.

Drawing on social marketing and humanistic management literature, this paper develops a framework for TSIs based on whether human dignity is recognized or ignored and whether a deficit-based or strength-based approach to vulnerability is used. This framework explains different types of TSIs and provides real-life examples.

The framework developed in this paper discusses four different types of TSIs: (1) exclusionary, a deficit-based approach where dignity is ignored; (2) opportunistic, a strength-based approach where dignity is ignored; (3) paternalistic, a deficit-based approach where dignity is recognized; and (4) humanistic, a strength-based approach where dignity is recognized. The paper also identifies five pathways that service organizations could use to implement these approaches, including two traps (utility and charity) and three opportunities (resourcing, humanizing and full awakening) embedded within these pathways.

This paper provides examples of service industries and specific companies to exemplify the framework developed. Also, it discusses the well-being implications and potential well-being outcomes associated with each type of TSI.

This paper offers a novel framework based on two dimensions that are relatively new to the service literature, i.e. dignity and vulnerability approach. This paper also highlights the importance of including these two dimensions in future service research.

This paper offers a novel framework based on two relatively new dimensions to the service literature: dignity and strengths-based approach. This paper also highlights the importance of including these two dimensions in future service research.

For over a decade now, various stakeholders in accounting education have called for the integration of technology competencies in the accounting curriculum (Association to Advance Collegiate Schools of Business (AACSB), 2013, 2018; Accounting Education Change Commission (AECC), 1990; American Institute of Certified Public Accountant (AICPA), 1996; Behn et al., 2012; Lawson et al., 2014; PricewaterhouseCoopers (PWC), 2013). In addition to stakeholder expectations, the inclusion of data analytics as a key area in both the business and accounting accreditation standards of the AACSB signals the urgent need for accounting programs to incorporate data analytics into their accounting curricula. This paper examines the extent of the integration of data analytics in the curricula of accounting programs with separate accounting AACSB accreditation. The paper also identifies possible barriers to integrating data analytics into the accounting curriculum. The results of this study indicate that of the 177 AACSB-accredited accounting programs, 79 (44.6%) offer data analytics courses at either the undergraduate or graduate level or as a special track. The results also indicate that 41 (23.16%) offer data analytics courses in their undergraduate curriculum, 61 (35.88%) at the graduate level, and 12 (6.80%) offer specialized tracks for accounting data analytics. Taken together, the findings indicate an encouraging trend, albeit slow, toward the integration of data analytics into the accounting curriculum.

This paper aims to present an approach for business organizations, especially multinational enterprises (MNEs), to pivot their focus from the United Nations sustainable development goals (UN SDGs) to simple doable goals (SDoGs) so that the probability of impactful and sustainable outcomes increases significantly.

Through multilevel analyses, the paper identifies the current challenges in the firm-level implementation of the SDGs. Consequently, it synthesizes an integrated solution that can help MNEs create sustainable business models, contributing to realizing the SDGs.

The sporadic and chaotic adoption of SDGs and ambiguous outcomes reported by businesses are due to the following: SDG adoption choices are driven by the materiality effect; the differences between the UN-defined government targets and business-level targets, often chosen by businesses on their own, make an aggregation of performances infeasible; lack of validation of the firm-level reporting leads to “greenwashing”; focusing less on business model transformation and more on reporting hinders the achievement of true sustainability; and lack of coordination and integration in actionizing among stakeholders limits the holistic change that the SDGs are expected to bring to society. Based on the Prêt à faire – Gestalt matrix, the proposed framework shifts the organization’s focus to the fundamental aspects of the purpose, strategy and business sustainability, and demonstrates how the resultant SDoGs effectively contribute to the realization of the SDGs. The matrix in the framework classifies an MNE based on its overall organizational readiness to seize business opportunities and helps pursue a course of action toward true sustainability.

The guidelines from the proposed framework offer different strategic paths for the MNE to achieve parity, temporary advantage, and, finally, sustained competitive advantage. This transformative approach enables businesses to develop their roadmaps for achieving business sustainability and supporting the realization of the SDGs.

The study presents a conceptual model of a firm's supply chain agility (FSCA) as a formative construct formed by sensing and responding capabilities. Both construct validity and predictive validity of the model are tested by investigating nuanced effects of FSCA on business performance. The study aims to empirically validate the sensing-responding theoretical framework of Overby et al. (2006) and extend the emergent stream on sensing-responding frameworks for supply chain agility.

Survey research is employed. Data are analysed using partial least squares technique and mediation tests by Hayes PROCESS macro.

FSCA is established as a revised construct formed by the distinct capabilities of sensing and responding. The efficacy of utilizing FSCA as a formative 2nd order construct was established. In addition, FSCA is shown to affect business performance through mediations of cost efficiency and customer effectiveness, establishing its predictive validity.

This study contributes significantly to the literature on supply chain agility in terms of both theory and practice for cultivating supply chain agility. Drawing on resource-based view and resource-advantage theories, as reformulation of supply chain agility as a formative construct of sensing and responding capabilities, this research opens up new lines of inquiry on agility.

The purpose of this paper is to examine how holistic thinking and the use of systems methodologies can help organisations handle increased problem complexity. The paper provides a critical discussion of the development of applied systems thinking and examines how its main strands can deal with problem complexity, multiple perceptions of reality and the unequal access to power resources in organisations.

The paper uses social theory and a systems meta-theoretical framework to examine the different ontological and epistemological assumptions that each strand of applied systems thinking makes about the nature of problems and the way in which an intervention will be made.

Complex problems require joined-up thinking and the use of systems ideas. Viewing the problem situation from a holistic perspective and applying appropriate systems methodologies and tools can help managers handle the complexities that their organisations face.

The paper makes a clear link between systems approaches and social theory and emphasises the need to understand the different assumptions that theories, methodologies or people make when they intervene in complex problem situations.

The insidious proliferation of online misinformation represents a significant societal problem. With a wealth of research dedicated to the topic, it is still unclear what determines fake news sharing. This paper comparatively examines fake and accurate news sharing in a novel experimental setting that manipulates news about terrorism.

The authors follow an extended version of the uses-and-gratification framework for news sharing, complemented by variables commonly employed in fake news rebuttal studies.

Logistic regression and classification trees revealed worry about the topic, media literacy, information-seeking and conservatism as significant predictors of willingness to share news online. No significant association was found for general analytical thinking, journalism skepticism, conspiracy ideation, uses-and-gratification motives or pass-time coping strategies.

The current results broaden and expand the literature examining beliefs in and sharing of misinformation, highlighting the role of media literacy in protecting the public against the spread of fake news.

This is, to the authors’ knowledge, the first study to integrate a breadth of theoretically and empirically driven predictors of fake news sharing within a single experimental framework.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-12-2022-0693