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Drawing attention to the significant number of unsuccessful (abandoned) cross-border merger and acquisition (M&A) transactions in recent years, the purpose of this paper is to analyze three litigated cross-border inbound acquisitions that associated with an emerging economy – India, such as Vodafone-Hutchison and Bharti Airtel-MTN deals in the telecommunications industry, and Vedanta-Cairn India deal in the oil and gas exploration industry. The study intends to explore how do institutional and political environments in the host country affect the completion likelihood of cross-border acquisition negotiations.

Nested within the interdisciplinary framework, the study adopts a legitimate method in qualitative research, that is, case study method, and performs a unit of analysis and cross-case analysis of sample cases.

The critical analysis suggests that government officials’ erratic nature and ruling political party intervention have detrimental effects on the success of Indian-hosted cross-border deals with higher bid value, listed target firm, cash payment, and stronger government control in the target industry. The findings emerge from the cross-case analysis of sample cases contribute to the Lucas paradox – why does not capital flow from rich to poor countries and interdisciplinary M&A literature on the completion likelihood of international takeovers.

The findings have several implications for multinational managers who typically involve in cross-border negotiations. The causes and consequences of sample cases would help develop economy firms who intend to invest in emerging economies. The study also offers some implications of M&A for telecommunications and extractive industries.

Although a huge amount of extant research investigates why M&A fail to create value to the shareholders during the public announcement and post-merger stages, there is a significant dearth of research on the causes and consequences of delayed or abandoned national and international deals. The paper fills this knowledge gap by discussing an in-depth cross-case analysis of Indian-hosted cross-border acquisitions.

Information and findings from investigations of construction projects using qualitative methodologies such as the grounded theory methodology (GTM) are inevitably rich. When using multiple case studies, the cross‐case analysis procedure has been found overwhelming and difficult to grasp all at once. Hence, an approach using rich picture diagrams (RPD) has been applied specifically for the purpose of modelling case studies and capturing the richness of the information along the case studies' storylines. This paper aims to explain the reasoning behind and the development process of such diagrams.

The paper investigates the underlying concepts of the GTM, case study approach, and the soft system methodology (SSM) from which the RPD was originally derived. Based on the identified agreement between and consistency of both methodologies, the development of RPD to model case studies in an ongoing research project (using the GTM) is explained. The subsequent cross‐case analysis procedure is also discussed, leading to conclusions.

The paper demonstrates the applicability of the RPD originating from the SSM as a tool to present the storylines of case studies within the GTM, to improve presentation and enable thorough cross‐case analysis by providing a holistic view of the storylines.

In response to the scholarly challenge to contribute to the further development of the GTM, the paper presents the application of a tool from SSM (i.e. the RPD). Whilst enriching the techniques within the GTM, this application provides a solution for researchers and stakeholders to model case studies of construction projects.

This section of the book comprises three chapters written by Oksana Grybovych, Susan Slocum, Ken Backman, Elisabeth Baldwin and Chris Ryan. The first two by Grybovych (2012) and Slocum, Backman, and Baldwin (2012) respectively report research processes related to specific projects, while the last seeks to provide an analysis associated with cross-case study research. By definition cross-case analysis relates to comparisons being made across different places, or of the same place across different times (a longitudinal analysis such as that by Gu & Ryan, 2008, 2011, in their studies of Shi Chi Hai Hutong in Beijing) or indeed of different places at different times, but related to each other by the commonality of a theme identified by the researcher.

This paper aims to identify and empirically analyze useful and applicable metrics for measuring and managing the sustainability performance of small and medium-sized enterprises (SMEs).

To achieve the objective of the paper, potential metrics were adopted from previous research related to industrial sustainability and an empirical analysis was carried to assess the applicability of the metrics by collecting empirical data from Italian footwear SMEs using a structured questionnaire. The SMEs were selected using a convenience sampling method.

The results of the within-case analysis and the cross-case analysis indicate that the majority of the metrics were found to be useful and applicable to each of the SMEs and across the SMEs, respectively. These metrics emphasized measuring industrial sustainability performance related to financial benefits, costs and market competitiveness for the economic sustainability dimension; resources for the environmental sustainability dimension; and customers, employees and the community for the social sustainability dimension.

Apart from the within-case analysis and cross-case analysis, it was not possible to conduct statistical analysis since a small number of SMEs were accessible to collect empirical data.

The findings of the paper have considerable academic, managerial and policy implications and will provide a theoretical basis for future research on measuring and managing industrial sustainability performance. By providing a set of empirically supported metrics based on the triple bottom line approach (i.e. economic, environmental and social metrics), this paper contributes to the existing knowledge in the field of industrial sustainability performance measurement.

This paper investigates the current state of green supply chain practices (GSCPs) and also introduces a framework for the implementation of GSCPs in India.

A case study approach was used for this research in which semi-structured interviews were conducted with three companies. These companies were automobile component manufacturing companies.

In the three case studies, there were different antecedents depending upon the specific company structure and organization. The ten GSCPs were used as a base for finding the antecedents.

Although every step has been taken to ensure the rigour and reliability of case studies, in a field as complex as GSCPs, there are inevitably some limitations. Due to the limited size of the case study approach, the results can only be generalized to a similar size and types of organization. The scope of data collection for all three case studies was the same, but the quality of information gathered varied. As demonstrated earlier, a good-quality cross-case analysis was still possible, but the relative strengths of the three cases varied.

A double contribution has been made to test the theory of GSCPs from a process and output perspective. From a process perspective, a contribution has been made to methodology by developing a robust approach for conducting supply chain research beyond the dyad. From an output perspective, the author has the empirical results from the three individual case studies and their cross-case comparison for dissemination to an academic audience.

The outputs of this research work will pave a path for other automobile component manufacturing companies in India to address and implement GSCPs.

A case‐based research approach is used to illustrate the power of modelling manufacturing performance measures and to help develop insights into the nature and problems evident when attempting to use simulation across different enterprise sectors. The research methodology used considered three specific companies, each with distinctive characteristics and attributes; a small to medium enterprise, a medium to large enterprise and a large enterprise. From a cross‐case analysis of the use of discreet‐event (DE) simulation when applied in these instances, the research attempts to develop policy implications that will provide a better understanding of how simulation studies should be approached across different manufacturing enterprises.

The purpose of this paper is to identify and examine the various mechanisms that can be used to integrate new technology into existing products, and to determine some of the conditions under which specific integration mechanisms are most appropriate.

The paper adopted an exploratory theory‐building approach based on analysis of data from 12 case studies, each representing companies with varying levels of: technological maturity of the organization and technological advancement of their products. Informants were managers and engineers who had responsibility for, or a significant role in, the integration of software and hardware. At least three interviews were conducted in each company and all interviews were of at least two hours duration. In total, 41 interviews were conducted. The different approaches used for technology integration were examined and subsequently mapped using the twin dimensions outlined above.

Cross‐case pattern analysis indicates that for technologically mature organizations, mechanisms based on processes are most appropriate, while for less mature organizations an approach based on structural mechanisms may be more suitable. Similarly, in cases involving high levels of technology advancement in the products, integration mechanisms based on processes and culture are preferable, whereas for low technology products the mechanisms are clustered around resource‐based approaches.

Multiple cases do not permit as much depth as the classic single case study and tend to yield “modest” rather than “grand” theoretical development. The use of scaling to convert qualitative data into quantitative data, and the identification of patterns in cross‐case analysis are both based on interpretive judgements. Future research should examine the proposed model and its constructs in different settings and using alternative research methods. There is also an opportunity to explore the relationships between the integration mechanisms and the outcomes of integration projects, and finally, it would be useful to extend the work to service settings and to integration of process technology.

The findings provide guidance to managers in selecting alternative approaches to managing the process of technology integration in different contexts. Examples are given of practices associated with each integration mechanism, together with some of the tensions and challenges which arise during implementation.

The paper provides clear guidance on the approaches that can be used for technology integration for product development. It classifies these according to the level of maturity and experience in the organization and the level of advancement of the product offered by the technology.

Managing supply‐chain operations is critical to any company’s ability to compete effectively. Success in today’s markets depends on the ability to balance a stream of products and processes to stay competitive. Companies are constantly evaluating every area of operations to ensure that productivity and cost objectives are realistic and attainable. Research has been carried out to investigate the measurement systems used in today’s distribution centers. Five distribution centers in the Pacific Northwest were selected for this study. The characteristics of these five distribution centers and their measurement systems are discussed in this paper. A cross‐case analysis is provided, which gives a view of a typical measurement system used in today’s distribution centers.

Despite the emergence and strategic importance of project risk management (PRM), its diffusion is limited mainly to large companies, leaving a lack of empirical evidence addressing SMEs. Given the socio-economic importance of SMEs and their need to manage risks to ensure the success of their strategic and innovative projects, this research aims to investigate how to adopt PRM in SMEs with a positive cost–benefit ratio.

This study presents an exploratory and explanatory research conducted through multiple-case studies involving 10 projects performed in Spanish and Italian small and medium-sized enterprises (SMEs).

The results obtained highlight how project features (commitment type, innovativeness, strategic relevance and managerial complexity) and firms' characteristics (sector of activity, production system and access to public incentives) influence PRM adoption, leading to different levels and types of benefits.

The paper offers practical indications about PRM phases, activities, tools and organizational aspects to be considered in different contexts to ensure the project's success and, ultimately, the company's growth and sustainability. Such indications could not be found in the literature.

This is an original piece of research holding the promise to position itself as a pioneering research to showcase the evolving role of Artificial intelligence (AI) in the Indian peer-to-peer lending (P2P) markets. The research effectively uses the holistic multiple case study design to highlight the phenomenon of how AI as the holy grail of investments is proving to be a game changer for the Indian P2P markets.

The study uses a unique research design and curates six Indian licensed Non-Banking Financial Company (NBFC)-P2P as exemplary cases to cull out unique contextual findings on how AI has penetrated the Indian P2P market and road ahead. The research is based on a total of 18 semi-structured interviews of six NBFC-P2P founders and 12 Fintech and P2P industry experts. These interviews were used as alternate sources of evidence for data triangulation along with within case analysis, cross-case analysis to achieve well-rounded results.

The findings have been propounded in the form of unique, context specific results achieved with a bouquet of six NBFC-P2P cases and supplemented through triangulation of data done through multiple industry experts. Findings indicate that AI has reached that tipping point in India.

There is a scope of further refinement of our results with a larger sample size. Therefore future researches could consider conducting a comprehensive study including all existing NBFC-P2Ps in the space.

The research builds perspective for improving the practice in many ways. It shows the way to the other P2Ps still stuck to manual underwriting and see merit in AI-driven processes. It would guide them to embrace new technology driven business models to enhance customer experience and champion service transformation by making financial processes faster and secure. It also highlights how some of the P2Ps are scaling up and improving their visibility and outreach through strategic partnerships.

The research would assist in creating awareness about the unique P2P sector and AI solutions for individual investors, particularly the “new to credit customers” and “thin file borrowers”. AI led initiatives in the P2P space validate a certain amount of sophistication thereby giving sanctity to the sector and would therefore enforce confidence in the minds of new age investors and borrowers.

This original research unravels avenues for novel and untraversed area in the Indian settings where paucity of extant literature and structured data highlighted a research gap and hence necessitated this study. AI as a form of disruptive innovation offering predictive intelligence to the Indian P2P space and empowering it with process efficiency, cost optimization and client engagement is definitely paving the way for an exponential growth in the Indian Fintech Industry.