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This study aims to draw a general framework for recreating water-related urban places. It discusses design criteria and processes that will strengthen people's and the city's relationship with the waterfront. It also explores the functional requirements of a participatory process to incorporate social and functional relations into place making.

The study is based on a comprehensive case study of the Kabataş project process. Data collection methods include archive searches, questionnaires, interviews and analysis. The study analyses the architectural decisions, the role and perspectives of the key actors and the current dynamics that shape the process. It points out shortcomings and needs of communication and collaboration with different stakeholders, especially with the users.

The results show that political and power dynamics play an important role in shaping the process. Non-transparent processes increase the gap between the aspects of community and decision makers in current practices. Establishing holistic, waterfront-specific and collaborative approaches is a necessity. The results also show that the success of participation depends on procedural dynamics such as scope, method, timing, representativeness of the community, institutionalisation level, transparency and deliberation.

Despite the intense interest in waterfront regeneration, few studies have focused on the potential of the participatory process. The study examines the intersections of waterfront design decisions and collaborative participation at various scales and emphasises the importance of local actors in the social production of space.

This paper aims to study the origin story of Harvard Business School’s involvement with the Indian Institute of Management Ahmedabad to study the reasons for the spread of American management education. It introduces both the explicit influence of Cold War politics and Indian development imaginaries to the export of American management thought in the early 1960s.

This paper relies on archival research for its primary source material, drawing upon rich archives of documents found at the Baker Library of Harvard Business School.

Harvard’s role in Ahmedabad was explicitly influenced by the Cold War anti-communist foreign policy of the USA, but did so opportunistically and contrary to the Ford Foundation’s (FF) original plans. Vikram Sarabhai, who was a key player in the Indian national imaginary of development, invited Harvard on his own initiative and forced the foundation to follow his interests rather than being a mere “subaltern.”

This paper could additionally add to the historical debate about the scope and periodization of the Cold War and the role of non-state actors.

This paper covers new ground in exploring the early connection between the Indian development imaginary and business education. It concludes that the export of hegemonic US management education was not successful during Cold War, and the FF was not as dominant as it was made out to be.

This paper offers a new perspective on the potential motivation for the adoption of employee ownership based on market power. Employee ownership may be linked to market power, either through contributing to firm growth that leads to market power or through industry leaders adopting employee ownership as part of rent sharing or a broader consolidation of market position. Both employee stock ownership plan (ESOP) coverage and product market concentration (PMC) have been increasing in the past two decades, providing a good opportunity to see if and how these are related.

The authors predict ESOP adoption and termination using multilevel regressions based on 2002–2012 firm- and industry-level data from the Census Bureau, Compustat and Form 5500 pension datasets.

The authors find that the top four firms in concentrated industries are more likely to adopt Employee Stock Ownership Plans (ESOPs), while having an ESOP does not predict entering the top four, apart from firm-level predictors. Tests indicate the first result does not reflect simple rent sharing with employees but instead appears to reflect an effort by firms to consolidate market power through the attraction and retention (or “locking in”) of industry talent. Other positive predictors of ESOPs include company size, being in a high-wage industry and having a defined benefit (DB) pension.

To better distinguish among hypotheses, it would be helpful to have firm-level data on managerial attitudes, strategies, networks and monopsony measures. Therefore, future research using such data would be highly useful and encouraged.

The paper includes implications for the potential usefulness of ESOPs in attracting and retaining talent and for the design of nuanced policy to encourage more broadly based sharing of economic rewards.

While prior research focuses on firm-level predictors of employee ownership, this study uses market concentration and other industry-level variables to predict the use of ESOPs. This study makes a unique contribution, broadening the current thinking on firm motives and environmental conditions predictive of firm ESOP adoption.

The advent of Internet of Things, cloud computing and advanced computing has endowed smart manufacturing environments with resilience, reconfigurability and intelligence, resulting in the emergence of novel capabilities. These capabilities have significantly reshaped the manufacturing ecosystem, enabling it to effectively navigate uncertainties. The purpose of this study is to assess the operational transformations resulting from the implementation of smart manufacturing, which distinguish it from conventional systems.

A list of qualitative and quantitative smart manufacturing performance metrics (SMPMs) are initially suggested and categorized into strategic, tactical and operational levels. The SMPMs resemble the capabilities of smart manufacturing systems to manage disruptions due to uncertainties. Then, industry and academia experts validate the SMPMs through the utilization of the Delphi method, enabling the ranking of the SMPMs.

The proposition of the SMPMs serves as a metric to assess the digital transformation capabilities of smart manufacturing systems. In addition, the ranking of the proposed SMPMs shows a degree of relevance of the measures in smart manufacturing deployment and managing the disruptions caused due to the COVID-19 pandemic

The findings benefit managers, consultants, policymakers and researchers in making appropriate decisions for deploying and operationalizing smart manufacturing systems by focusing on critical SMPMs.

The research provides a metric to assess the operational transformations during the deployment of smart manufacturing systems. Also, it states the role of the metric in managing the potential disruptions that can alter the performance of the business due to the COVID-19 pandemic.

This article aims at - exploring and prioritizing the barriers to adoption of digitization in supply chains (SCs), categorizing them into sustainability triple bottom line (STBL) based upon their direct impact and suggesting digital technologies to address each barrier.

A five-phase methodology is used which consists of an exploration of 44 barriers to the adoption of digitization in SCs, analysis of 44 barriers for mean, standard deviation and Cronbach alpha based on questionnaire-based feedback of 25 experts, extraction of 10 most significant barriers through 05 experts, followed by categorization of the barriers into STBL referring to their direct impact on STBL, prioritization of ten barriers using Fuzzy Technique for Order Performance by Similarity to Ideal Solution and recommendation of digital technologies to address each barrier.

While all the barriers considered in this study significantly impede the adoption of digitization in SCs, lack of top management commitment (B1) is found to be most crucial while lack of culture toward use of information and communication technology required for digitization (B3) has minimum impact. Large investment in digital infrastructure (B6), difficulty in integration of cyber physical systems (CPSs) on varied platforms (B8) and lack of experts having knowledge of digital technologies (B2) are equally important barriers requiring more attention while adopting digitization in SCs.

This study is mainly based on feedback from 25 seasoned experts; a wider cross section of experts will give more insight.

The outcomes are very significant for organizations looking to adopt digitization in their SCs. Simultaneous consideration to all the barriers becomes impractical hence prioritization of same will be useful for the SC managers to benchmark their preparedness and decide strategies for the adoption of digitization with due consideration toward the impact of barriers on STBL. The digital technologies recommended will further aid in planning the digital strategies to address each barrier.

A unique approach to explore, analyze, prioritize and categorize the barriers to adoption of digitization in SCs is used to provide a deeper understanding of factors deterring the same. It implies that a supportive top management along with systematic allocation of finances plays a crucial role. The importance of availability of digital experts for integrating CPSs on a single platform is also highlighted. The digital technologies recommended will further assist the organizations toward adoption of digitization in SCs with due consideration to STBL.

This study aims to develop a modular and prescriptive digital transformation maturity model whose constituent elements have conceptual integrity as well as reveal the priority weights of maturity model components.

A literature review with a concept-centric analysis enlightens the characteristics of constituent parts and reveals the gaps for each component. Therefore, the interdependency network among model dimensions and priority weights are identified using decision-making trial and evaluation laboratory (DEMATEL)-based analytic network process (ANP) method, including 19 industrial experts, and the results are robustly validated with three different analyses. Finally, the applicability of the developed maturity model and the constituent elements are validated in the context of the manufacturing industry with two case applications through a strict protocol.

Results obtained from DEMATEL-based ANP suggest that smart processes with a priority weight of 17.91% are the most important subdimension for reaching higher digital maturity. Customer integration and value, with a priority weight of 17.30%, is the second most important subdimension and talented employee, with 16.24%, is the third most important subdimension.

The developed maturity model enables companies to make factual assessments with specially designed measurement instrument including incrementally evolved questions, prioritize action fields and investment strategies according to maturity index calculations and adapt to the dynamic change in the environment with spiral maturity level identification.

A novel spiral maturity level identification is proposed with conceptual consistency for evolutionary progress to adapt to dynamic change. A measurement instrument that is incrementally structured with 234 statements and a measurement method that is based on the priority weights and leads to calculating the maturity index are designed to assess digital maturity, create an improvement roadmap to reach higher maturity levels and prioritize actions and investments without any external support and assistance.

Industry 4.0 is characterised by systemic transformations occurring exponentially, encompassing an array of dynamic processes and technologies. To move towards a more sustainable future, it is important to understand the nature of this transformation. However, construction enterprises are experiencing a capacity shortage in identifying the transitional management steps needed to navigate Industry 4.0 better. This paper presents a maturity model with the acronym “Smart Modern Construction Enterprise Maturity Model (SMCeMM)” that provides direction to construction enterprises.

It adopts an iterative procedure to develop the maturity model. The attributes of Industry 4.0 maturity are obtained through a critical literature review. The model is further developed through knowledge elicitation using modified Delphi-based expert forums and subsequent analysis through qualitative techniques. The conceptual validity of the model is established through a validation expert forum.

The research defines maturity characteristics of construction enterprises across five levels namely ad-hoc, driven, transforming, integrated and innovative encompassing seven process categories; data management, people and culture, leadership and strategy, automation, collaboration and communication, change management and innovation. The maturity characteristics are then translated into assessment criteria which can be used to assess how mature a construction enterprise is in navigating Industry 4.0.

The results advance the field of Industry 4.0 strategy research in construction. The findings can be used to access Industry 4.0 maturity of general contractors of varying sizes and scales and generate a set of recommendations to support their macroscopic strategic planning.

We studied the relationship between job engagement and systematic problem solving (SPS) among shop-floor employees and how lean production (LP) and Internet of Things (IoT) systems moderate this relationship.

We collected data from a sample of 440 shop floor workers in 101 manufacturing work units across 33 plants. Because our data is nested, we employed a series of multilevel regression models to test the hypotheses. The application of IoT systems within work units was evaluated by our research team through direct observations from on-site visits.

Our findings indicate a positive association between job engagement and SPS. Additionally, we found that the adoption of lean bundles positively moderates this relationship, while, surprisingly, the adoption of IoT systems negatively moderates this relationship. Interestingly, we found that, when the adoption of IoT systems is complemented by a lean management system, workers tend to experience a higher effect on the SPS of their engagement.

One limitation of this research is the reliance on the self-reported data collected from both workers (job engagement, SPS and control variables) and supervisors (lean bundles). Furthermore, our study was conducted in a specific country, Italy, which might have limitations on the generalizability of the results since cross-cultural differences in job engagement and SPS have been documented.

Our findings highlight that employees’ strong engagement in SPS behaviors is shaped by the managerial and technological systems implemented on the shop floor. Specifically, we point out that implementing IoT systems without the appropriate managerial practices can pose challenges to fostering employee engagement and SPS.

This paper provides new insights on how lean and new technologies contribute to the development of learning-to-learn capabilities at the individual level by empirically analyzing the moderating effects of IoT systems and LP on the relationship between job engagement and SPS.

Significant developments in the service sector have been brought about by Industry 4.0. Automated digital technologies make it possible to upgrade existing services and develop modern industrial services. This study prioritizes critical factors for adopting Industry 4.0 in the Indian service industries.

The author identified four criteria and fifteen significant factors from the relevant literature that have been corroborated by industry experts. Models are then developed by the analytical hierarchy process (AHP) and analytical network process (ANP) approach to ascertain the significant factors for adopting Industry 4.0 in service industries. Further, sensitivity analysis has been conducted to determine the sensitivities of the rank of criteria and sub-factors to corroborate the results.

The outcome reveals the top significant criteria as organizational criteria (0.5019) and innovation criteria (0.3081). This study prioritizes six significant factors information technology (IT) specialization, digital decentralization of all departments, organizational size, smart services through customer data, top management support and Industry 4.0 infrastructure in the transition toward Industry 4.0 in the service industries.

The potential factors identified in this study will assist managers in determining strategies to effectively manage the Industry 4.0 transition by concentrating on top priorities when leveraging Industry 4.0. The significance of organizational and innovation criteria given more weight will lay the groundwork for future Industry 4.0 implementation guidelines in service industries.

Our research is novel since, to our knowledge, no previous study has investigated the potential critical factors from organizational, environmental, innovation and cost dimensions. Thus, the potential critical factors identified are the contributions of this study.

Food manufacturing companies which are essential for national economies, need to attach importance to the adoption of both the lean manufacturing (LM) operational excellence methodology and the Industry I4.0 (I4.0) technologies that empower LM to achieve operational improvement. This study aims to focus on the Greek food manufacturing companies and determine the degree of implementation of LM practices and I4.0 technologies and the impact of I4.0 on LM.

A survey was conducted based on a structured questionnaire which included items reflecting LM practices and I4.0 technologies. A sample of Greek food manufacturing companies were approached and 102 of them fully completed the questionnaire. Descriptive statistics were applied to determine the degree of implementation of LM practices and I4.0 technologies, while the impact of I4.0 on LM was determined through the linear regression analysis.

The degree of implementation of LM practices in the responding food manufacturing companies is high, while the degree of implementation of I4.0 technologies is low to medium. The findings also support a significant and positive impact of I4.0 on LM.

The small size of the sample of the responding Greek food manufacturing companies, the subjective character of the data collected and the cross-sectional nature of the study, constitute the main limitations of the study. Based on these limitations, further studies can be designed.

The present study findings can guide the managers of the food manufacturing companies to further increase the degree of implementation of LM practices through adopting I4.0 technologies. Therefore, they can improve quality, eliminate waste, survive and be more competitive in the current difficult business environment. Academics can also benefit from the present study, given that it provides the LM practices and I4.0 technologies that can be further tested and validated in the food sector.

To the best of the authors’ knowledge, this is the first study that focuses on LM and I4.0 in the Greek food manufacturing companies operating in a business environment where the crises of finance, energy and the Covid-19 pandemic dominate.