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Digital twins provide enormous opportunities for smart buildings. However, an up-to-date intellectual landscape to understand and identify the major opportunities of digital twins for smart buildings is still not enough. This study, therefore, performs an up-to-date comprehensive literature review to identify the major opportunities of digital twins for smart buildings.

Scientometric and content analysis are utilised to comprehensively evaluate the intellectual landscape of the general knowledge of digital twins for smart buildings.

The study uncovered 24 opportunities that were further categorised into four major opportunities: efficient building performance (smart “building” environment), efficient building process (smart construction site environment), information efficiency and effective user interactions. The study further identified the limitations of the existing studies and made recommendations for future research in the methodology adopted and the research domain. Five research domains were considered for future research, namely “real-time data acquisition, processing and storage”, “security and privacy issues”, “standardised and domain modelling”, “collaboration between the building industry and the digital twin developers” and “skilled workforce to enable a seamless transition from theory to practice”.

All stakeholders, including practitioners, policymakers and researchers in the field of “architecture, engineering, construction and operations” (AECO), may benefit from the findings of this study by gaining an in-depth understanding of the opportunities of digital twins and their implementation in smart buildings in the AECO industry. The limitations and the possible research directions may serve as guidelines for streamlining the practical adoption and implementation of digital twins for smart buildings.

This study adopted scientometric and content analysis to comprehensively assess the intellectual landscape of relevant literature and identify four major opportunities of digital twins for smart building, to which scholars have given limited attention. Finally, a research direction framework is presented to address the identified limitations of existing studies and help envision the ideal state of digital twins for smart buildings.

The dynamism of competition in international markets requires managers to react accordingly and ensure the firm's survival and competitiveness. This study examines the impact of cognitive styles and dynamic managerial capabilities (DMC) on a firm's international performance and the mediating role of these capabilities in the relationship between cognitive styles and international performance.

This study adopts a quantitative cross-sectional research design, employing a sample of 306 firm owner-managers from exporting companies in Kosovo.

The findings suggest that managers' cognitive styles positively influence firm international performance, including their impact on DMC. Results also indicate that only managerial cognition mediates cognitive styles' effects on a firm's international performance, compared to managers' social capital.

In this study, the authors contribute to the literature by integrating cognitive styles with DMC in a transition country. Moreover, the authors demonstrate that DMC mediate the impact of cognitive styles on the firm international performance.

Upon completion of this case study, students should be able to apply lessons learned in core readings, analysis and discussion to a specific case study dealing with a current, real-world situation, specifically: critically assess Livestock Wealth’s case facts and present and justify their point of view – based on attentive reading, critical analysis and engagement – about the company; use a range of strategic tools such as strengths, weaknesses, opportunities and threats analysis, PESTLE analysis and the Ansoff matrix to thoroughly evaluate Livestock Wealth’s internal and external business environment for developing strategic options for business growth and improvements to marketing strategy; use strategic thinking to develop a range of creative solutions to guide the company’s business growth and improvements to marketing strategy; and assess their own growth and development in terms of personal preparation and organisation, collaboration, critical thinking, decision-making skills, participation and problem-solving.

By February 2022, Ntuthuko Shezi, the founder and chief executive officer of Livestock Wealth, had turned his idea of “crowd farming”, which enables anyone to invest in living farm assets and earn a profit at harvest, into a full-fledged business that was creating wealth for both investors and farmers. Underpinning this case study is Shezi’s vision of an African continent where there is “no ground that is not planted with something of value”, local economies are created in those areas, communities are wealthy, there is abundance, there is money for children to attend school and ultimately where “cows (and agricultural produce in general) are seen as money”. Shezi had grown up in a rural area with grandparents who owned a couple of cows, realizing that the cows were the bedrock of the family’s finances. Describing his business, he says, “Cattle are like a walking bank, and we see ourselves as the bank of the future, where every person who owns a cow can access financial services through Livestock Wealth, just like it has always been in Africa.” This case study describes the two key decisions that Shezi needed to make – what direction to take in terms of business growth and how to improve his marketing strategy (with a limited budget) to attract sufficient investment into Livestock Wealth to make his dreams a reality.

This case study is suitable for use for a post-graduate diploma in business, master of business administration or master’s in management.

Teaching notes are available for educators only.

CSS 11: Strategy.

This paper aims at measuring the factors affecting early-stage entrepreneurial activity by opportunity vs necessity motives in India using theory of planned behaviour.

The study is based on the Adult Population Survey (APS) of Global Entrepreneurship Monitor (GEM), covering 4,165 respondents in 2018. The data has been analysed using descriptive statistics, chi-square test, analysis of variance and logistics regression. The theory of planned behaviour has been used to identify the determinants of early-stage entrepreneurial activity by opportunity vs necessity motives.

About 13.1% of the respondents reported early-stage entrepreneurial activity, of which opportunity motives were reported by 6.5% respondents, necessity motives by 5.4% respondents and the remaining 1.2% respondents reported other motives. Further, the mean difference in early-stage entrepreneurial activities by motives shows the domination of opportunity-driven entrepreneurial activities. Finally, marginal effects of all determining variables and three components of the theory of planned behaviour, i.e. attitude towards entrepreneurship (ATE), perceived subjective norm (PSN) and perceived behavioural control (PBC), have been estimated on opportunity vs necessity motives of early-stage entrepreneurial activities.

This paper contributes theoretically and practically to the existing body of knowledge by predicting the factors affecting opportunity vs necessity motives of early-stage entrepreneurial activities by applying the theory of planned behaviour. Considering the current focus of the government on promoting entrepreneurship, this piece of research can be valuable in adopting a motive-based approach in implementing entrepreneurial initiatives.

This paper provides unique insights into developing a policy framework for promoting new ventures based on the perceived motives of the entrepreneurs.

When improving business processes, process analysts can use data-driven methods, such as process mining, to identify improvement opportunities. However, despite being supported by data, process analysts decide which changes to implement. Analysts often use process visualisations to assess and determine which changes to pursue. This paper helps explore how process mining visualisations can aid process analysts in their work to identify, prioritise and communicate business process improvement opportunities.

The study follows the design science methodology to create and evaluate an artefact for visualising identified improvement opportunities (IRVIN).

A set of principles to facilitate the visualisation of process mining outputs for analysts to work with improvement opportunities was suggested. Particularly, insights into identifying, prioritising and communicating process improvement opportunities from visual representation are outlined.

Prior work focuses on visualisation from the perspectives – among others – of process exploration, process comparison and performance analysis. This study, however, considers process mining visualisation that aids in analysing process improvement opportunities.

This chapter focusses on analysing the origins and evolution of the SWOT analysis. It explains the drivers and limitations of the conventional SWOT analysis, laying the groundwork for new decision-making models that can aid researchers and practitioners in comprehending both the external landscape and the internal characteristics of a company. This chapter demonstrates how the strengths, weaknesses, opportunities, and threats of the SWOT analysis can be approached dynamically. Conventional SWOT analysis offers only a limited perspective on the environment and employs terminology that can confuse users, hindering their clear understanding of the factors that influence an organisation’s situation. This chapter provides a concise literature review of tools for evaluating quality management, its resources, and the surrounding environment, which serves as a valuable means to grasp the economic and social context within which a firm operates.

The Internet of Things (IoT), as one of the new digital technologies, has created wide applications in various industries, and one of the most influential industries of this technology is the transportation industry. By integrating the IoT with the transportation industry, there will be dramatic changes in the industry, and it will provide many entrepreneurial opportunities for entrepreneurs to develop new businesses. Opportunity identification is at the heart of the entrepreneurial process, and entrepreneurs identify innovative goods or services to enter a new market by identifying, evaluating, and exploiting opportunities. Despite the desire of transportation managers to invest in the IoT and the increase in research in this area, limited research has focused on IoT-based entrepreneurial opportunities in the transportation industry. Therefore, the present study aims to identify IoT-based entrepreneurial opportunities in the transportation industry and examine their importance.

To achieve the research objective, the authors applied a mixed approach. First, adapting the lens of the industry value chain theory, a comprehensive literature review, besides a qualitative approach including semi-structured interviews with experts and thematic analysis, was conducted to identify the entrepreneurial opportunities. The identified opportunities were confirmed in the second stage using a quantitative survey method, including the Student t-test and factor analysis. Finally, the identified opportunities were weighted and ranked using the best worst method (BWM).

Entrepreneurial opportunities are classified into five main categories, including “smart vehicles”, “business partners/smart transportation supply side”, “supporting services”, “infrastructures”, and “smart transport management and control”. The infrastructures group of opportunities ranked the highest amongst the identified groups.

This study adds to the digital entrepreneurship opportunity recognition literature by addressing opportunities in a smart industry propelled by digital technologies, including developing new products or new applications of the available technologies. Additionally, inspired by the industry value chain theory, this article develops a framework including various digital entrepreneurial opportunity networks which are necessary to add value to any industry and, thus, could be applied by entrepreneurs to recognize opportunities for new intermediaries to enter other digital-based industries. Finally, the present study identifies the IoT-based entrepreneurial opportunities in the smart transportation industry and prioritizes them, providing practical insights regarding the creation of entrepreneurial ecosystems in the field of smart transportation for entrepreneurs and policymakers.

Although the significance of technological progress in economic development is well-established in theory and policy, it has remained challenging to agree upon shared priorities for strategies and policies. This paper aims to develop a model of how policymakers can develop effective and easy to communicate strategies for science, technology and economic development.

By integrating insights from economic complexity, competitiveness and foresight literature, a replicable research framework for analysing the opportunities and challenges of technological revolutions for small catching-up countries is developed. The authors highlight key lessons from piloting this framework for informing the strategy and policies for bioeconomy in Estonia towards 2030–2050.

The integration of economic complexity research with traditional foresight methods establishes a solid analytical basis for a data-driven analysis of the opportunities for industrial upgrading. The increase in the importance of regional alliances in the global economy calls for further advancement of the analytical toolbox. Integration of complexity, global value chains and export potential assessment approaches offers valuable direction for further research, as it enables discussion of the opportunities of moving towards more knowledge-intensive economic activities along with the opportunities for winning international market share.

The research merges insights from the economic complexity, competitiveness and foresight literature in a novel way and illustrates the applicability and priority-setting in a real-life setting.

The purpose is to use co-citation analysis of servant leadership (SL) research to investigate the evolution of the field, its subfields, gaps and opportunities for future research in a systematic manner.

A document co-citation technique and three clustering algorithms (latent semantic index (LSI), the log-likelihood ratio (LLR) and the mutual information (MI) index) were employed to analyse 24,030 references from 549 articles spanning a period of 50 years.

Cluster analyses reveal that SL research consists of eight distinct subfields: (1) conceptualisation and measurement of SL; (2) SL and related theories; (3) methodological foundations and empirical expansion of SL research; (4) individual-level cognitive effects of SL and related theories; (5) “Warmth effects” of leadership behaviour; (6) antecedents of effective leadership; (7) SL, marketing, sales management and ethics and (8) SL, job design and work engagement. Important gaps and opportunities for future research are identified.

The analyses do not show a complete picture of research on SL. Interesting works used by subgroups of SL researchers may not have enough citations to be included in the results. Moreover, bibliometric analyses do not explain the impact of books, journals and articles on the practice of SL. The authors welcome future analyses of the most influential sources of SL practice. The authors expect that managerial and practice-oriented books and journals, such as the International Journal of Servant Leadership and the Servant Leadership Theory and Practice, would play a central role in such analyses.

The discussions of the nature of SL, its effects and antecedents are useful to leaders who want to develop a SL style or assist others in developing it. For researchers and doctoral students, the cluster analyses of co-citations give an overview of the subfields of SL research and reveal important knowledge gaps in the literature.

SL has several favourable effects on the motivation and psychological well-being of followers. Also, followers tend to adopt a willingness to serve.

Previous research has categorised SL research into three broad categories or phases. The cluster analyses of the co-citations reported here reveal a meaningful structure of eight distinct subfields. Knowledge gaps within the subfields represent novel opportunities for future research on SL. The authors also suggest a new subfield of SL research: pedagogical approaches to the motivation and development of SL skills.