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Despite an enormous body of literature on conflict management, intra-group conflicts vis-à-vis team performance, there is currently no study investigating the conflict prevention approach to handling innovation-induced conflicts that may hinder smooth implementation of big data technology in project teams.

This study uses constructs from conflict theory, and team power relations to develop an explanatory framework. The study proceeded to formulate theoretical hypotheses from task-conflict, process-conflict, relationship and team power conflict. The hypotheses were tested using Partial Least Square Structural Equation Model (PLS-SEM) to understand key preventive measures that can encourage conflict prevention in project teams when implementing big data technology.

Results from the structural model validated six out of seven theoretical hypotheses and identified Relationship Conflict Prevention as the most important factor for promoting smooth implementation of Big Data Analytics technology in project teams. This is followed by power-conflict prevention, prevention of task disputes and prevention of Process conflicts respectively. Results also show that relationship and power conflicts interact on the one hand, while task and relationship conflict prevention also interact on the other hand, thus, suggesting the prevention of one of the conflicts could minimise the outbreak of the other.

The study has been conducted within the context of big data adoption in a project-based work environment and the need to prevent innovation-induced conflicts in teams. Similarly, the research participants examined are stakeholders within UK projected-based organisations.

The study urges organisations wishing to embrace big data innovation to evolve a multipronged approach for facilitating smooth implementation through prevention of conflicts among project frontlines. This study urges organisations to anticipate both subtle and overt frictions that can undermine relationships and team dynamics, effective task performance, derail processes and create unhealthy rivalry that undermines cooperation and collaboration in the team.

The study also addresses the uncertainty and disruption that big data technology presents to employees in teams and explore conflict prevention measure which can be used to mitigate such in project teams.

The study proposes a Structural Model for establishing conflict prevention strategies in project teams through a multidimensional framework that combines constructs like team power conflict, process, relationship and task conflicts; to encourage Big Data implementation.

The advent of artificial intelligence (AI) in the accounting landscape marks a significant shift, promising gains in efficiency and accuracy but also eliciting concerns about job displacement (JD) and broader socio-economic implications. This study aims to provide an in-depth understanding of how AI’s integration in accounting contributes to JD, reshapes decision-making processes and reverberates across economic and social dimensions. It also offers evidence-based policy recommendations to mitigate adverse outcomes.

Leveraging a cross-sectional survey disseminated through Facebook, this research used snowball sampling to target a diverse cohort of accounting professionals. The collected data were subjected to meticulous analysis through descriptive and regression models, facilitated by SmartPLS 4 software.

The analysis revealed a significant correlation between AI’s increasing role in accounting and a heightened rate of JD. This study found that this displacement is not isolated; it has tangible repercussions on decision-making paradigms, economic well-being, professional work dynamics and social structures. These insights corroborate existing frameworks, including, but not limited to, theories of technological unemployment and behavioural adjustments.

Although providing valuable insights, this study acknowledges limitations such as the restricted sample size, the cross-sectional nature of the survey and the inherent biases of self-reported data. Future research could aim to extend these initial findings by adopting a longitudinal approach and potentially integrating external data sources.

As AI technology becomes increasingly ingrained in accounting practices, there is an urgent need for coordinated action among stakeholders. Policy recommendations include focused efforts on talent retention, investment in upskilling programs and the establishment of support mechanisms for those adversely affected by AI adoption.

By synthesising a range of theoretical perspectives, this study offers a comprehensive exploration of AI’s multi-dimensional impacts on the accounting profession. It stands out for its nuanced examination of JD and its economic and social implications, thereby contributing to both academic discourse and policy formulation. This work serves as an urgent call to action, highlighting the need for strategies that both exploit AI’s potential benefits and protect the workforce from its disruptive impact.

Frontline workers (FLWs) constitute a critical part of the implementation cadre within public policies, serving a significant role in the last-mile delivery of public goods and services. FLWs under public programs in low and middle-income countries like India are offered different compensation structures that range from full-time salaries, piece rate honorariums, contractual engagements, to no remuneration. Whilst the rationale for offering different compensations vary, are certain structures more successful in encouraging FLWs to perform a prosocial task? Further, can certain structures encourage FLWs to perform beyond the incentivized policy mandate?

Investigating workers' prosocial effort within policy implementation, the authors conducted a randomized lab-in-the-field inquiry with 344 Anganwadi-based workers (workers under the nutrition policy) in western India. These FLWs were engaged to perform a novel real-effort task that was tied to different incentive structures and their performance was adjudged based on measurable quantity, effort and quality parameters.

Results demonstrate that uncompensated workers invest the greatest amount of effort whilst compromising on task quality, and vice-versa for subjects receiving pay-for-performance compensation. Programs must account for policy focus when offering compensations: volunteer engagement may be counterproductive for quality focus and to the adherence to ancillary task mandates like nature/quality of beneficiary interaction. On the other hand, the distribution of products (like health goods) can rely on volunteer effort.

The study brings together various compensation schemes operating at the field level, under one study using an LFE methodology within the context of policy implementation in India.

Land value in urban areas in India is influenced by regulations, bylaws and the amenities associated with them. Planning interventions play a significant role in enhancing the quality of the neighbourhood, thereby resulting in a change in its value. Land is a distinct commodity due to its fixed location, and planning interventions are also specific to certain locations. Consequently, the factors influencing land value will vary across different areas. While recent literature has explored some determinants of land value individually, conducting a comprehensive study specific to each location would be more beneficial for making informed policy decisions. Therefore, this article aims to examine and identify the critical factors that impact the value of residential land in the National Capital Territory of Delhi, India.

The study employed a combination of semi-structured and structured interview methods to construct a Relative Importance Index (RII) and ascertain the critical determinants affecting residential land value. A sample of 36 experts, comprising property valuers, urban planners and real estate professionals operating within the National Capital Territory of Delhi, India, were selected using snowball sampling techniques. Subsequently, rank correlation and ANOVA methods were employed to evaluate the obtained results.

Location and stage of urban development are the most critical determinants in determining residential land values in the National Capital Territory of Delhi, India. The study identifies a total of 13 critical determinants.

A scenario planning approach can be developed to achieve an equitable distribution of values and land use entropy. A land value assessment model can also be developed to assist professional valuers.

There has been a lack of emphasis on assessing the impact of planning interventions and territorial regulation on land values in the context of Delhi. This study will contribute to policy decision-making by developing a rank list of planning-based determinants of land value.

In Chapter 1, we critically reviewed the foundations of the free enterprise capital system (FECS), which has been successful primarily because of its wealth and asset accumulation potentiality and actuality. In this chapter, we critically argue that this capacity has been grounded upon the profit maximization (PM) theories, models, and paradigms of FECS. The intent of this chapter is not anti-PM. The PM models of FECS have worked and performed well for more than 200 years of the economic history of the United States and other developed countries, and this phenomenon is celebrated and featured as “market performativity.” However, market performativity has not truly benefitted the poor and the marginalized; on the contrary, market performativity has wittingly or unwittingly created gaping inequalities of wealth, income, opportunity, and prosperity. Critical thinking does not combat PM but challenges it with alternative models of profit sharing that promote social wealth, social welfare, social progress, and opportunity for all, which we explore here. Economic development without social progress breeds economic inequality and social injustice. Economic development alone is not enough; we should create a new paradigm in which economic development is the servant of social progress, not vice versa. Such a paradigm shift involves integrating the creativity and innovativity of market performativity and the goals and drives of social performativity together with PM, that is, from market performativity to social performativity.

This paper utilizes generativity to explore the relationship between mentoring support and organizational identification, turnover intention and reciprocated mentoring in protégés.

The paper used a cross-sectional design with surveys administered to 351 working adults in the USA to test the hypotheses on the relationship between mentoring and turnover intention through organizational identification with first-stage moderation of generativity.

Employees who were high in generativity, mentoring support was positively associated with organizational identification and negatively associated with turnover intentions. Generativity was also positively related to reciprocated mentoring through the choice to mentor others, the number of mentees and the mentoring support provided.

The authors' results suggest organizations receive the greatest benefits when providing mentoring support to generative employees.

This study applies generativity to the context of mentoring by exploring the impact of mentoring support on identification with the organization, turnover intentions and willingness to mentor others by comparing the conditional effects of high generativity versus low generativity.

The competition in the academe has always been tough, but today, the academe seems to be more like an industry than an academic community as academics are evaluated through quantified and economic means.

This article leans on Heidegger’s thoughts on the essence of technology and his ontological view on being to show the dangers that lie in this quantification of researchers and research.

Despite the benefits that information systems (ISs) offer to people and research, it seems that technology has made it possible to objectify researchers and research. This has a negative impact on the academe and should thus be looked into especially by the IS field, which should note the problems that exist in its core. This phenomenon of quantified academics is clearly visible at academic quantification sites, where academics are evaluated using metrics that count their output. It seems that the essence of technology has disturbed the way research is valued by emphasising its quantifiable aspects. The study claims that it is important to look for other ways to evaluate researchers rather than trying to maximise research production, which has led to the flooding of articles that few have the time or interest to read.

This paper offers new insights into the current phenomenon of quantification of academics and underlines the need for critical changes if in order to achieve the academic culture that is desirable for future academics.

The case is written based on publicly available data from primary sources such as the company’s annual reports, company website and the company’s presentations, as well as from secondary sources comprising newspaper articles, research papers, research magazines, magazine articles, industry reports, research reports, etc. as indicated in the references. The company’s financials and peer data are sourced from the Thomson Reuters Eikon database.

The case examines the financial position of Macy’s, Inc., America’s largest and one of the oldest premier departmental stores, with a consolidated annual turnover of US$18,097m in the fiscal year 2020/2021 (FY, 2021). Over the previous few years, the company had been struggling with decreasing market share and profitability mainly due to increasing competition from online retailers and deep discounters, which was affecting the company’s share price. With the appointment of a new chief executive officer (CEO) in fiscal year (FY) 2017, Macy’s, Inc. undertook several changes to revive its financial health and improve its market share. However, it still registered heavy losses of US$3,944m in the FY 2020/2021, the company’s first time in the past decade. With many retailers filing for bankruptcy, was there more that Macy’s could do to improve the company’s position and regain lost investor confidence? Will its entry into emerging markets play a crucial role in its turnaround?

The case can be used in undergraduate and postgraduate courses such as accounting for managers, financial statement analysis, management accounting, introduction to accounting and advanced financial statement analysis. The case can also be effectively used to understand the primary fundamental analysis of the company that involves understanding the company’s positioning and strengths, weaknesses, opportunities and threats analysis. The case would also help business management and entrepreneurship students to get a preliminary idea about the change management process. Finally, the case can be used to familiarize students with using Microsoft Excel to build financial analysis worksheets.

Teaching notes are available for educators only.