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The purpose of this research was to study senior and middle-level executive perspectives on ethical decision-making exploring stakeholder cross-impact analysis (SCIA). Given the complexities of business today, stakeholder identification, prioritisation and complexities of reciprocal stakeholder influences have become very important. Various philosophical approaches raised questions than responses to these problems. There was a clear need to find ways through which the worldview of agents could be assimilated and understood.

This study used the original hypothetical short case and brought in middle and senior executive reflections of Indian fast-moving consumer goods (FMCG) managers. Reflections of ten senior and 178 middle-level Indian FMCG managers were presented, exploring ethical dilemmas using short hypothetical case. These reflections have been analysed using the SCIA framework. The paired t-test was performed to compare the reflections of senior and middle-level executives.

The study results indicated that differences emerged regarding stakeholder identification, prioritisation and reciprocal stakeholder influences between Indian middle and senior FMCG executives. Hence, this study paved a reflective space for SCIA. The findings were in line with the tenets of agents’ dilemmas depicted in agency theory.

This study made contribution to theory by integrating the perspective of ethical dilemma confronted by organisational decision-making units (DMUs) with respect to stakeholder influence and prioritisation. Specifically, theoretical contribution was made towards SCIA.

This study would help middle and senior executives to better understand the needs and complexities of stakeholder identification, prioritisation and complexities of reciprocal stakeholder influences.

To the best of the authors’ knowledge, this was one of the first studies from an emerging market context country like India that applied SCIA in the FMCG sector. Organisational DMUs while facing ethical dilemma undertook stakeholder influence vis-a-vis stakeholder prioritisation.

The paper intends to show why farms as we know them today may soon be a thing of the past and that organisational behaviour research has an important contribution to make in assisting the upcoming transformation.

Two strains of literature are reviewed and then synthesised: the literature on robots replacing humans in agricultural production and the literature on vertical integration that shifts decisions to agribusiness. Then the potential contribution of organisational behaviour research is outlined.

It is shown how the farm is likely to lose both roles for which their geographic entity is important: making decisions and carrying out production. This requires contributions from organisational behaviour research in the realms of decision designs and social systems.

It can be anticipated that the most profitable strategy for farmland owners in the future will be collaboration with contractors. Farms as organisations, are increasingly losing their importance. This not only has grave social implications for farmworkers and landowners but also for scholars in organisational behaviour research.

The paper challenges an organisational unit that is so familiar to us that it is rarely questioned.

This research investigates the critical role of data governance (DG) in shaping a data-driven culture (DDC) within organizations, recognizing the transformative potential of data utilization for efficiency, opportunities, and productivity. The study delves into the influence of DG on DDC, emphasizing the mediating effect of data literacy (DL).

The study empirically assesses 125 experienced managers in Indonesian public service sector organizations using a quantitative approach. Structural Equation Modeling (SEM) analysis was chosen to examine the impact of DG on DDC and the mediating effects of DL on this relationship.

The findings highlight that both DG and DL serve as antecedents to DDC, with DL identified as a crucial mediator, explaining a significant portion of the effects between DG and DDC.

Beyond unveiling these relationships, the study discusses practical implications for organizational leaders and managers, emphasizing the need for effective policies and strategies in data-driven decision-making.

This research fills an important research gap by introducing an original model and providing empirical evidence on the dynamic interplay between DG, DL, and DDC, contributing to the evolving landscape of data-driven organizational cultures.

This study aims to examine the impact of governance on project delivery in complex private finance initiative (PFI) projects. Governance is crucial in delivering successful projects within budget, time and in accordance with other project objectives.

A two‐stage approach was used to address the research questions. First, a literature review was carried out and second, a multiple case study approach based on detailed semi‐structured interviews with project directors and senior managers was conducted to provide an in‐depth insight on how two major PFI projects were planned, managed and delivered in the National Health Service (NHS, UK).

Project governance influences project delivery in terms of cost, speed of completion, quality and its financial viability as it is critical in providing clear organisational structure, effective decision‐making structures and control processes. The success of one scheme was attributed to an appropriate governance structure enabling necessary reviews and adjustments to be made to render the scheme financially viable and affordable. The failed scheme, subsequently abandoned at a cost of over £15 million to tax payers, was due to an inadequate governance structure creating conflicting priorities of stakeholders, complex decision making with negative impact on project deliverables such as cost and time.

Previous research has not addressed the management aspect of governance which has a significant influence on financial outcomes of NHS PFI schemes. This will enable NHS and other public client organisations to understand the need for adequate governance structure in reducing the risks of projects running over time and incurring increase costs to ensure financial viability and affordability, particularly in large complex schemes.

The purpose of this paper is to investigate the organizational aspects of an open innovation approach by focusing on the relationship between universities and firms as a vehicle for acquiring technological knowledge. It discusses in detail the characteristics of firm organizational units that are devoted to managing relationships with universities and the processes that firms put in place to select research fields and partners.

Considering the complex system of variables that characterize this phenomenon, an interview‐based case study method is adopted. In order to compare behaviors and organizational approaches, a retrospective, multiple case study method with theoretical replication was employed to focus on four companies that operate in three different industries: telecoms, construction, and aviation. The goal was to better explain the studied phenomenon. After the data‐gathering phase, the cases were compared by identifying similarities and differences in terms of four different drivers, the relevance of which were highlighted during the interviews.

First, the sampled companies do acquire external knowledge from universities, but in doing so, they take into account the technology lifecycle (or s‐curve) and its associated phases. Second, in order to manage relationships with universities, companies make different decisions vis‐à‐vis four main organizational variables: the number of people involved in the organizational unit (OU) that is devoted to managing relationships with universities; the positioning of the OU within (or outside) the firm's boundaries; the degree of work specialization in the OU; and the degree of formalization of the process.

This paper is one of the first attempts to operationalize the open innovation concept from an organizational perspective. Thus, it opens new possibilities for future organization‐focused studies on this topic.

Within the organizational literature, the emphasis on group performance has tended to overshadow issues of group composition and structure. In this chapter we urge group scholars to turn their attention to the topic of hierarchy in organizational groups. We focus on hierarchy as defined by both status and power. We propose that understanding how organizational groups resolve conflicts, make decisions, and ultimately perform, must stem from an understanding of the hierarchical structure in the team. Hierarchy imposes constraints on group interactions and should therefore be more central in our frameworks, theories, and research. We look at three areas that could benefit from bringing a hierarchical perspective to the forefront: (1) Information exchange and discussion biases in group decision making, (2) The study of conflict management and negotiation, and (3) Creativity and effectiveness in diverse teams.

British construction industry KPI data collected over recent years shows a trend in projects exceeding their time schedules. In 2013, the UK Government set a target for projects timeframes to reduce by 50 per cent. Proposed interventions included more rapid project delivery processes, and consistent improvements to construction delivery predictions, deployed within the framework of 4D Building Information Modelling (BIM). The purpose of this paper is to use Rogers’ Innovation Diffusion theory as a basis to investigate how this adoption has taken place.

In total, 97 construction planning practitioners were surveyed to measure 4D BIM innovation take-up over time. Classic innovation diffusion research methods were adopted.

Results indicated an increasing rate of 4D BIM adoption and reveal a time lag between awareness and first use that is characteristic of this type of innovation.

Use of a non-probability sampling strategy prevents the results being generalisable to the wider construction population. Future research directions and methods are suggested, including qualitative investigations into decision-making processes around 4D BIM, and case studies exploring the consequences of 4D BIM adoption.

Recommendations of how to facilitate the adoption of 4D BIM innovation are proposed, which identify the critical aspects of system compatibility and safe trialling of the innovation.

This paper reinforces 4D BIM as an innovation and records its actual UK industry adoption rate using an accepted diffusion research method. By focusing on UK industry-wide diffusion the work also stands apart from more typical research efforts that limit innovation diffusion exploration to individual organisations.

The main objective of the paper is to develop an investment model using data envelopment analysis (DEA) that provides a decision-making framework to allocate resources efficiently, such that the relative efficiency is improved within an available investment budget.

Firstly, DEA models are used to evaluate the efficiency of the departments relative to their peers and providing benchmarks for the less efficient departments. Secondly, the inefficiencies in departments are identified. Finally, for the less efficient departments, a decision-support system is introduced for optimizing resource allocation to improve efficiency.

Five of the 18 academic departments were determined to be inefficient, and benchmark departments were found for those departments. The most prevalent causes for inefficiency were the number of undergraduate students per faculty and the number of graduate students. Results from the investment model for department 12 suggest increasing the number of faculty by 2 units and H-Index by 0.5 units, thereby, improving the relative efficiency of the department by 6.8% (88%–94%), using $290,000 out of $500,000 investment budget provided.

When an investment budget is available, no study has used DEA to develop a decision-support framework for resource allocation in academic departments to maximize relative efficiency.

The purpose of this paper is to develop and test a structural model of the factors that explain the level of perceived relationship effectiveness between marketing managers and sales managers.

The model integrates trust‐based and power/influence/interdependence‐based models of relationship effectiveness. The data were collected from 113 sales managers in the UK and Australia. Confirmatory factor analysis was used to test the validity of the measures, while AMOS Version 4 was employed to estimate the model using structural equation modelling with observed variables.

The study found, on average, that the perceived level of relationship effectiveness between sales managers and marketing managers is surprisingly high. The findings clearly demonstrate the potency of interpersonal trust (both cognition‐based and affect‐based) in building effective cross‐functional relationships (CFRs) and also show how interdependence affects both dimensions of trust and the marketing manager's level of manifest influence. In addition, the findings indicate that, when marketing managers have greater manifest influence, the CFR is more effective. Importantly, evidence is provided regarding the consequences of marketing managers using the two influence tactics of legalistic pleas and threats, in terms of their effects on trust and manifest influence. Finally, insights are given about the sequencing of these two influence tactics and how the power of the marketing unit indirectly affects relationship effectiveness.

This is one of the very few studies to use a large empirical survey to examine the marketing and sales dyad.

The discussion on energy efficiency has been increasing due to the increasing population, emissions of degradable and harmful pollutants, and clean energy substitutes are being developed in order to manage and control the energy requirements all over the world. Against this backdrop, the factors of technological innovation and environmental regulations have been determined as key indicators for the evaluation of sustainable developments and practices in the energy efficiency evaluation studies.

A two-stage analysis process has been configured for evaluation of the energy efficiency. The first stage includes the estimation of the Total factor energy efficiency scores using the data envelopment Multiplier input-oriented methodology, while the second stage includes the exploration of the impact of technological innovation and government environmental regulations on the Total factor energy efficiency scores obtained in the first step through the application of a spatial regression model.

This paper highlights the link between the need for and impact of energy efficiency innovations and shows that the energy efficiency goal can be fulfilled by incorporating laws on sustainability and incorporating strict regulations that allow for the use of clean energy, low carbon energy technologies.

The present study, furthermore, provides evidence from 15 countries, five from three different continents, i.e. Asia, Europe and Africa so that a cross-country performance of these factors can be evaluated. The main contribution of the present study is the evaluation of the technological innovation on energy efficiency. There have been studies evaluating various factors on the development of energy-efficient practices; however, the focus on the role of technological innovation and governmental regulations has been scarce.