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The purpose of this paper is to identify and analyze the interdependence of project complexity factors (PCFs) in metro rail projects using the Decision-Making Trial and Evaluation Laboratory (DEMATEL). The study provides qualitative and quantitative analysis of project complexities factors and their relationships. The results of the study facilitate effective project planning, proactive risk management and informed decision-making by stakeholders.

This study employs a case-based method for identifying PCFs and a DEMATEL method for analyzing the interdependence of complexity factors in metro rail projects. Initially, PCFs were identified through an extensive literature review. To validate and refine these factors, semi-structured interviews were conducted with thirty experienced professionals, each having 5–20 years of experience in roles such as project management, engineering, and planning. Further, elevated and underground metro rail projects were purposefully selected as cases, for identifying the similarities and differences in PCFs. A questionnaire survey was conducted with various technical experts in metro rail projects. These experts rated the impact of PCFs on a five-point Likert scale, for the evaluation of the interdependence of PCFs. The DEMATEL technique was used to analyze the interdependencies of the PCFs.

Metro rail projects are influenced by project complexity, which significantly impacts their performance. The analysis reveals that “design problems with existing structures,” “change in design or construction” and “land acquisition” are the key factors contributing to project complexity.

The study of project complexity in metro rail projects is limited because most of the studies have studies on examining complexity in mega projects. The existing literature lacks adequate attention in identifying project complexity and its effects on metro rail project performance. This research aims to bridge this gap by examining project complexity and interdependencies in metro rail projects.

Through the significance matrix, this paper aims to investigate and explore the main sustainability factors of mega transportation infrastructure projects. Sydney’s Metro mega transportation infrastructure is used as a case study. Sydney’s Metro was selected because of its sustainability challenges faced because of the areas’ diverse ecological zones. Sydney’s Metro is thus examined as the basis of best practice for the determination of the sustainability factors of transportation infrastructures.

Using the significance matrix as a methodology, this research evaluates the environmental impact assessment and environmental assessment processes, to alleviate the problems of the mega transportation infrastructure.

This research found that a more comprehensive determination is needed to further analyse the sustainability factors of mega transportation infrastructures, use of a significance matrix would further assess the environmental complexities of mega transportation infrastructures and the sustainability factors of mega transportation infrastructures should include a nonlinear and asymmetrical scheme highlighting its components and carefully outlining its integration and consolidation.

Although there is concurrent research into sustainability factors of mega transportation, this paper undertakes a new methodology for such infrastructure. While the significance matrix is not a new concept, it has never been used specifically for mega transportation infrastructure. Subsequently, using the significance matrix as a methodology, this research undertakes such environmental analysis and assessment and thus produces a qualitative risk analysis matrix. The findings from this research will ultimately assist the key stakeholders of mega transportation infrastructures to better plan, monitor and support similar projects.

The use of technology in 4th industrial revolution is at its peak. Industries are trying to reduce the consumption of resources by effectively utilizing information and technology to connect different functioning agents of the manufacturing industry. Without digitization “Industry 4.0” will be a virtual reality. The present survey-based study explores the factual status of digital manufacturing in the Northern India.

After an extensive literature review, a questionnaire was designed to gather different viewpoints of Indian industrial practitioners. The first half contains questions related to north Indian demographic factors which may affect digitalization of India. The latter half includes the queries concerned with various operational factors (or drivers) driving the digital revolution without ignoring Indian constraints.

The focus of this survey was to understand the current level of digital revolution under the ongoing push by the Indian government focused upon digital movement. The analysis included non-parametric testing of the various demographic and functional factors impacting the digital echoes, specifically in Northern India. Findings such as technological upgradations were independent of type of industry, the turnover or the location. About 10 key operational factors were thoughtfully grouped into three major categories—internal Research and Development (R&D), the capability of the supply chain and the capacity to adapt to the market. These factors were then examined to understand how they contribute to digital manufacturing, utilizing an appropriate ordinal logistic regression. The resulting predictive analysis provides seldom-seen insights and valuable suggestions for the most effective deployment of digitalization in Indian industries.

The country-specific Industry 4.0 literature is quite limited. The survey mainly focuses on the National Capital Region. The number of demographic and functional factors can further be incorporated. Moreover, an addition of factors related to ecology, environment and society can make the study more insightful.

The present work provides valuable insights about the current status of digitization and expects to facilitate public or private policymakers to implement digital technologies in India with less efforts and the least resistance. It empowers India towards Industry 4.0 based tools and techniques and creates new socio-economic dimensions for the sustainable development.

The quantitative nature of the study and its statistical predictions (data-based) are novel. The clubbing of similar success factors to avoid inter-collinearity and complexity is seldom seen. The predictive analytics provided in this study is quite elusive as it provides directions with logic. It will help the Indian Government and industrial strategists to plan and perform their interventions accordingly.

Urban rail projects are typically large-scale transport infrastructure projects (megaprojects) which have many potential risks that can influence the strategic goals of owners. However, there is a paucity of studies which explore the impact of risks on both “urban rail” project time and cost together considering quantitative assessments. Therefore, this paper focuses on investigating critical risks and quantifying such risk impacts on urban railway project schedule and cost in practice.

A combination of qualitative and quantitative research methods comprising semi-interviews with five experts and a questionnaire survey of 132 professional respondents is used. The data were modeled using Monte Carlo Simulation to predict the probability of project schedule and cost.

The results show that 30 risk variables are categorized into seven main groups which have significant impacts on both project time and cost. Outstanding five risk variables were highlighted as follows: (1) project site clearance and land compensation; (2) design changes; (3) physical project resources; (4) contractors’ competencies and (5) project finance. Such findings were supported by Monte Carlo simulation which predicted in the worst case that the project may suffer 11.03 months’ delays and have cost overrun with a contingency of US$287.68 million.

This study expands our knowledge about time and cost contingency of urban metro railway implementation across developing economies and particularly within the context of Vietnam. Policymakers will not only gain an understanding about risk structure but will also recognize the significant impacts of critical risk through risk impact modeling and simulation. Such an approach provides insights into risk treatment priorities for planners so that they can proactively establish suitable strategies for risk mitigation in practice.

This paper contributes insights into how different firm types in the emerging market (EM) of Turkey respond to upgrading pressures in terms of internationalization and the usage of domestic political support. It seeks to highlight how the usage of and the responses to different strategies, connections and policy instruments vary with firm types.

Binary logistic regression analysis is used to differentiate and identify characteristics of firms regarding market-seeking strategies and their usage of institutional and financial support. The analysis is based on survey data from firms located in the metro-region of Istanbul: advanced market multinational enterprises (AMNEs), Turkish MNEs (TMNEs) and domestic Turkish firms (DTFs).

Different types of firms within the population of innovative firms in the EM setting of Turkey show significant variety regarding the usage of and the responses to key factors affecting internationalization. AMNEs particularly benefit from investment and export incentives as well as from establishing political connections in Turkey. DTFs significantly use tax incentives and primarily seek advanced markets. TMNEs particularly benefit from investment and export incentives and prefer to target advanced markets.

Using Turkey as a single-country setting is a limitation to the generalizability of the results. Future studies could use more cases of AMNEs to compare different countries of origin. In addition, the intended focus on R&D-related firms produces specific outcomes for such companies.

National and regional policies need to pursue different strategies for the surveyed groups of firms to attract and maintain foreign direct investments (FDIs) of AMNEs as well as to support outward FDIs of domestic firms and EM MNEs. In particular, policies for market entries and knowledge sourcing in advanced markets are becoming a crucial factor for EM firms in overcoming a shortage of resources at home.

This paper’s findings challenge existing theories such as the concept of psychic distance or liabilities of foreignness, which do not always provide an adequate explanation for internationalization activities of EM firms. In addition, it is highly relevant to apply an eclectic or multidimensional concept when conducting research in EMs in order to capture the interrelated constructs of upgrading, internationalization and political support.

This review aims to give a critical view of the wheel/rail high frequency vibration-induced vibration fatigue in railway bogie.

Vibration fatigue of railway bogie arising from the wheel/rail high frequency vibration has become the main concern of railway operators. Previous reviews usually focused on the formation mechanism of wheel/rail high frequency vibration. This paper thus gives a critical review of the vibration fatigue of railway bogie owing to the short-pitch irregularities-induced high frequency vibration, including a brief introduction of short-pitch irregularities, associated high frequency vibration in railway bogie, typical vibration fatigue failure cases of railway bogie and methodologies used for the assessment of vibration fatigue and research gaps.

The results showed that the resulting excitation frequencies of short-pitch irregularity vary substantially due to different track types and formation mechanisms. The axle box-mounted components are much more vulnerable to vibration fatigue compared with other components. The wheel polygonal wear and rail corrugation-induced high frequency vibration is the main driving force of fatigue failure, and the fatigue crack usually initiates from the defect of the weld seam. Vibration spectrum for attachments of railway bogie defined in the standard underestimates the vibration level arising from the short-pitch irregularities. The current investigations on vibration fatigue mainly focus on the methods to improve the accuracy of fatigue damage assessment, and a systematical design method for vibration fatigue remains a huge gap to improve the survival probability when the rail vehicle is subjected to vibration fatigue.

The research can facilitate the development of a new methodology to improve the fatigue life of railway vehicles when subjected to wheel/rail high frequency vibration.

This case study outlines the strategic and organisational issues faced by an entrepreneurial firm operating in an emerging economy. This case study has been written to equip students with how entrepreneurs can overcome certain barriers and use technology to achieve product–market fit, taking the Indian laundry sector as an example. The following are the key learnings for the case: start-ups need to continuously assess the product–market fit to organise a highly unorganised sector; market entry and expansion modes require proper evaluation of available entry and expansion modes before pursual; franchising decisions require firm-specific and location-specific considerations; and careful consideration given to celebrity endorsement will result in increased sales.

The Indian laundry market was a highly unorganised market and presented an untapped opportunity. While the market opportunity was enormous, the existing solutions comprised local vendors that may not provide end-to-end services (washing, ironing, etc.). The case study described how a young entrepreneur, Arunabh Sinha, overcame certain challenges to achieve a product–market fit for metro cities and later expanded to Tier 2 and Tier 3 cities in India as well. However, the challenges remained, as the firm expanded by using a franchise model, and other modes of business were required to be evaluated as well.

The case study is suitable for students pursuing MBA courses in marketing, service marketing and entrepreneurship development.

Teaching notes are available for educators only.

CSS3: Entrepreneurship.

Recent scholarship has explored higher education institutions’ (HEIs) role in transitioning to a sustainable society, but empirically, questions remain regarding their impact on the sustainability of surrounding areas. This study aims to examine the correlation between HEIs’ sustainability actions and local sustainability performance.

This study uses a linear regression model and principal component analysis to examine the sustainability performance of 105 US metropolitan statistical areas (MSAs) using the US cities sustainable development goal (SDG) index, which hosts 427 HEIs known for sustainability efforts. The weighted HEI sustainability performance score is calculated based on the QS sustainability universities ranking.

The correlation between MSA and HEI sustainability performance exhibits a mix of positive and negative associations, with individual and interlinked SDGs serving as proxies. These correlations encompass a wide range of goals, from economic aspects of SDG 1, 2, 3, 7, 9, social aspects of SDG10 and 16, to socio-environmental aspects of SDG12.

Further exploration is needed to identify the causal mechanisms behind associations between SDG measures and HEI sustainability performance, whether influenced by the institution, the individual or both.

This study suggests that HEIs are already associated with some aspects of community sustainability, but greater contributions to a broader array of sustainability measures are possible.

The correlation found between HEI sustainability actions and SDG10, 12 and 16 index performance in an MSA highlights a connection between HEIs and the attainment of societal goals.

To the best of the authors’ knowledge, this study is the first to examine the correlation between HEI and MSA sustainability performance in the US through individual and interlinked SDG proxies. It provides novel empirical evidence that demonstrates an association between HEI and some aspects of community sustainability performance.

This study aims to examine the differential impact of ride-hailing services (RHS) on private and commercial vehicle ownership from five metropolitan cities in India.

Using vehicle ownership data from five metropolitan cities over period 1991 to 2020, a panel corrected standard errors model was estimated to model the association between RHS and vehicle ownership.

The results indicate that advent of RHS has led to a significant reduction in private vehicle ownership rates and a corresponding increase in addition of intermediate public transport. The net effects of RHS on road congestion and pollution levels need to be studied in detail.

The findings of this study can potentially assist policymakers and mobility planners in efforts to decarbonise and decongest urban transport.

This study sets precedence in analysing the impact of RHS on private and commercial vehicle independently. Further, to the best of the author’s knowledge, this is the first study to examine this association for the city of Delhi and Kolkata.

In the realm of disaster risk reduction (DRR) efforts and disaster resilience discipline globally, the impacts of disasters at the family level – especially in terms of interpersonal relationships – remain largely understudied. This paper aims to explore the impacts of postdisaster relocation on the internal dynamics of families in Southville 7 in Calauan, Laguna, Philippines during the aftermath of the 2009 typhoon Ketsana, and endeavors to inform institutional policies to strengthen families’ disaster resilience.

Purposive sampling was applied in choosing the 20 participating families for the case study of Site III, Southville 7 – a relocation site housing more than 3,000 displaced families from Metro Manila during typhoon Ketsana. Data gathering methods such as semistructured interviews and personal observations were used during fieldwork, the findings of which were coded to reveal the study’s analytical themes.

Research findings reveal that the impacts of postdisaster relocation to family dynamics could be classified into seven broad categories: family composition and structure; members’ roles; parenting; parents’ marital relationship; familial relationship; family member’s personalities; and death and disabilities. The interplay between these impacts results in either stronger overall family cohesion or further relational ruptures.

By spotlighting the impacts of disasters on overall family dynamics in the context of postdisaster relocation, this study seeks to elevate the place of the family in the DRR and disaster resilience discourse.