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To investigate ethnographically how patient experience data, as a named category in healthcare organisations, is actively “made” through the co-creative interactions of data, people and meanings in English hospitals.

The authors draw on fieldnotes, interview recordings and transcripts produced from 13 months (2016–2017) of ethnographic research on patient experience data work at five acute English National Health Service (NHS) hospitals, including observation, chats, semi-structured interviews and documentary analysis. Research sites were selected based on performance in a national Adult Inpatient Survey, location, size, willingness to participate and research burden. Using an analytical approach inspired by actor–network theory (ANT), the authors examine how data acquired meanings and were made to act by clinical and administrative staff during a type of meeting called a “learning session” at one of the hospital study sites.

The authors found that the processes of systematisation in healthcare organisations to act on patient feedback to improve to the quality of care, and involving frontline healthcare staff and their senior managers, produced shifting understandings of what counts as “data” and how to make changes in response to it. Their interactions produced multiple definitions of “experience”, “data” and “improvement” which came to co-exist in the same systematised encounter.

The article's distinctive contribution is to analyse how patient experience data gain particular attributes. It suggests that healthcare organisations and researchers should recognise that acting on data in standardised ways will constantly create new definitions and possibilities of such data, escaping organisational and scholarly attempts at mastery.

The purpose of this paper is to map out the Indian nanotechnology innovation system. An attempt is made to identify the dominant actors, collaborative pattern and analyse the role of and interactions between the actors and institutions.

A combination of frameworks such as national and international system of innovation is used to include all possible actors and institutions involved. A scientometric analysis is also carried out.

Despite a series of government interventions discernible in various programmes since the 1980s, nanotechnology-based industries are yet to emerge as a dominant sector. The health sector has emerged as one of the major contributors in terms of nanotechnology applications. There are many other challenges of safety and standards, socioeconomic, ethical and environmental concerns. Academic R&D labs are active in technology transfer.

A scant literature is available for this sector in India and especially from the international innovation system framework to analyse the socioeconomic and risk governance issues.

A scant literature is available for this sector in India and especially from the international innovation system framework to analyse the socioeconomic and risk governance issues.

A scant literature is available for this sector in India and especially from the international innovation system framework to analyse the socioeconomic and risk governance issues.

This paper aims to explore how intra-industry entrepreneurial experience and failure entrepreneurial experience affect novelty-centered business model design in a new venture. Moreover, the authors also consider whether the contingent value of entrepreneurial experience may differ according to competitive intensity.

A survey via questionnaire was conducted with 290 entrepreneurs and top managers from Chinese new ventures that provided the research data. Hierarchical regression analysis was used to test the proposed theoretical hypotheses.

The empirical results indicate that intra-industry entrepreneurial experience has an inverted U-shaped effect on novelty-centered business model design, whereas failure entrepreneurial experience has a negative effect on novelty-centered business model design. Furthermore, the authors also find that competitive intensity weakens the inverted U-shaped effect of intra-industry entrepreneurial experience on novelty-centered business model design.

This study offers new insights into the effects of intra-industry entrepreneurial experience and failure entrepreneurial experience on novelty-centered business model design and provides useful suggestions for new ventures to promote business model design.

Each individual needs to be vaccinated to control the spread of the COVID-19 pandemic in the shortest possible time. However, the vaccine distribution with an already strained supply chain in low- and middle-income countries (LMICs) will not be effective enough to vaccinate all the population in stipulated time. The purpose of this paper is to show that there is a need to revolutionize the vaccine supply chain (VSC) by overcoming the challenges of sustainable vaccine distribution.

An integrated lean, agile and green (LAG) framework is proposed to overcome the challenges of the sustainable vaccine supply chain (SVSC). A hybrid best worst method (BWM)–Measurement of Alternatives and Ranking According to COmpromise Solution (MARCOS) methodology is designed to analyze the challenges and solutions.

The analysis shows that vaccine wastage is the most critical challenge for SVSC, and the coordination among stakeholders is the most significant solution followed by effective management support.

The result of the analysis can help the health care organizations (HCOs) to manage the VSC. The effective vaccination in stipulated time will help control the further spread of the virus, which will result in the normalcy of business and availability of livelihood for millions of people.

To the best of the author's knowledge, this is the first study to explore sustainability in VSC by considering the environmental and social impact of vaccination. The LAG-based framework is also a new approach in VSC to find the solution for existing challenges.

Studies on organizational failure learning have focused on whether and how organizations learn from failures but have paid limited attention on the persistence of failure learning. This study centers on failure recidivism and answers why organizations would fall into repeated failures after learning from them.

Based on a sample of Chinese publicly listed firms that once recovered from special treatment status, the authors use event history technique and Cox proportional hazards regression model.

The authors find that reviviscent firms with higher interlock centrality are less likely to decline again, and underperforming partners can strengthen the role of interlock tie in failure recidivism. By contrast, politically connected reviviscent firms are more likely to decline again, and this effect attenuates for firms located in more market-oriented regions.

The authors’ contribution comes from the close integration of literature on failure learning and network embeddedness perspective to examine how social networks affect the learning process of failure recidivism.

The study provides important practical implications for organizations, especially those that once experienced failures or are experiencing failures.

Combining organizational learning theory and network embeddedness perspective, the study provides novel insights into answering how firms embedded in different types of social networks affect failure learning persistence differently.

Cloud computing (CC) refers to the usage of virtualization technology to share computing resources through the internet. Task scheduling (TS) is used to assign computational resources to requests that have a high volume of pending processing. CC relies on load balancing to ensure that resources like servers and virtual machines (VMs) running on real servers share the same amount of load. VMs are an important part of virtualization, where physical servers are transformed into VM and act as physical servers during the process. It is possible that a user’s request or data transmission in a cloud data centre may be the reason for the VM to be under or overloaded with data.

VMs are an important part of virtualization, where physical servers are transformed into VM and act as physical servers during the process. It is possible that a user’s request or data transmission in a cloud data centre may be the reason for the VM to be under or overloaded with data. With a large number of VM or jobs, this method has a long makespan and is very difficult. A new idea to cloud loads without decreasing implementation time or resource consumption is therefore encouraged. Equilibrium optimization is used to cluster the VM into underloaded and overloaded VMs initially in this research. Underloading VMs is used to improve load balance and resource utilization in the second stage. The hybrid algorithm of BAT and the artificial bee colony (ABC) helps with TS using a multi-objective-based system. The VM manager performs VM migration decisions to provide load balance among physical machines (PMs). When a PM is overburdened and another PM is underburdened, the decision to migrate VMs is made based on the appropriate conditions. Balanced load and reduced energy usage in PMs are achieved in the former case. Manta ray foraging (MRF) is used to migrate VMs, and its decisions are based on a variety of factors.

The proposed approach provides the best possible scheduling for both VMs and PMs. To complete the task, improved whale optimization algorithm for Cloud TS has 42 s of completion time, enhanced multi-verse optimizer has 48 s, hybrid electro search with a genetic algorithm has 50 s, adaptive benefit factor-based symbiotic organisms search has 38 s and, finally, the proposed model has 30 s, which shows better performance of the proposed model.

User’s request or data transmission in a cloud data centre may cause the VMs to be under or overloaded with data. To identify the load on VM, initially EQ algorithm is used for clustering process. To figure out how well the proposed method works when the system is very busy by implementing hybrid algorithm called BAT–ABC. After the TS process, VM migration is occurred at the final stage, where optimal VM is identified by using MRF algorithm. The experimental analysis is carried out by using various metrics such as execution time, transmission time, makespan for various iterations, resource utilization and load fairness. With its system load, the metric gives load fairness. How load fairness is worked out depends on how long each task takes to do. It has been added that a cloud system may be able to achieve more load fairness if tasks take less time to finish.

The case illustrates the challenges of managing JVs in emerging markets. specifically, after going through the case, students should be able to: i.Analyze the contexts in which firms need to form JVs and evaluate this need in the context of emerging markets such as India; ii.Understand how multinational corporations can achieve success in emerging markets, specifically the role of strategic (broader than the product) adaptation in success; iii.Evaluate the impact of conflict between partners on the short-term and long-term performance of a JV; and iv.Create alternatives, evaluate each alternative’s pros and cons, and recommend appropriate decisions to address the situation after a JV unravels and the organization is faced with quality and other challenges.

McDonald’s, the global giant in the quick service industry, entered India in 1993 and formed two JVs in 1995 one with Vikram Bakshi (Connaught Plaza Restaurants Ltd or CPRL) to own and operate stores in the northern and eastern zones, and another with Amit Jatia (Hardcastle Restaurants Private Limited or HRPL) to own and operate stores in the western and southern zones. Over the next 12 years, both the JVs made steady progress by opening new stores while also achieving better store-level metrics. Though CPRL was ahead of HRPL in terms of the number of stores and total revenues earned in 2008, the year marked the beginning of a long-running dispute between the two partners in CPRL, Bakshi and McDonald’s. Over the next 11 years, Bakshi and McDonald’s tried to block each other, filed court cases against each other and also exchanged recriminations in media. The feud hurt the performance of CPRL, which fell behind HRPL in terms of growth and other metrics. On May 9, 2019, the feuding partners reached an out-of-court settlement under which McDonald’s would buy out Bakshi’s shares in CPRL, thus making CPRL a subsidiary. Robert Hunghanfoo, who had been appointed head of CPRL after Bakshi’s exit, announced a temporary shutdown of McDonald’s stores to take stock of the current situation. He had to make a number of critical decisions that would impact the company’s performance in the long-term.

MBA, Executive MBA and executive development programs.

Teaching Notes are available for educators only.

CSS 11: Strategy.

The apparel industry of Bangladesh is rethinking lean manufacturing (LM) deployment because of the challenges imposed by the COVID-19 pandemic. Due to COVID-19, LM implementation in the apparel industry has become more difficult. Thus, the purpose of this study is to explore the barriers to implementing LM practices in the apparel industry of Bangladesh in the context of COVID-19 pandemic.

For evaluating the barriers, an integrated framework that combines the Delphi method and fuzzy total interpretive structural modeling (TISM) has been designed. The application of fuzzy TISM has resulted in a structured hierarchical relationship model of the barriers with driving and driven power.

The findings reveal that “lack of synchronization of lean planning with strategic planning”, “lack of proper understanding of lean concept” and “low priority from the top management” are the three top most important barriers of LM implementation in apparel industry.

These findings will help the apparel industry to formulate strategy for implementing the LM practices successfully. The proposed model is expected to contribute to the sustainable development goals (SDGs) such as Responsible Consumption and Production (SDG 12); Decent Work and Economic Growth (SDG 8); Industry, Innovation and Infrastructure (SDG 9) via resilient strategies.

This study is one of few initial efforts to investigate LM implementation barriers during the COVID-19 epidemic in a real-world setting.

This study aims to examine the impact of founder or descendant chief executive officers (CEOs) on the relationship between tax avoidance and firms' future risk. This issue is important because of an ongoing debate about founder and descendant CEOs' impacts, contributions and implications for firms.

This study uses a sample of publicly listed nonfinancial Indonesian firms in 2012–2019, most of which are family firms and adhere to a two-tier governance system that was understudied in previous studies. The authors use panel-random effect data regression for the statistical analysis.

The results demonstrate that founder or descendant CEOs do not affect the positive relationship between tax avoidance and firms' future risks.

This research supports the upper-echelon theory, arguing that top management teams affect firms' strategic policies and outcomes.

CEOs play weaker roles in countries with a two-tier governance system than in a one-tier one. Additionally, in relation to Hofstede's cultural dimensions, Indonesia has collective and feminist characteristics that emphasize elements of togetherness and group so that firms reflect the firms' top management teams and not only CEOs.

This research fills a research gap on the role of founder and descendant CEOs in the relationship between tax avoidance and firms' future risks by analyzing firms in Indonesia, a country with a two-tier governance system and collective and feminine cultural characteristics.

The purpose of this research paper is to identify the enablers for Lean implementation in the manufacturing sector, to establish a relationship among them using interpretive structural modeling (ISM) and to rank them using interpretive ranking process (IRP).

The research paper presents a blend of theoretical framework and practical applications. In the paper, eight enablers of Lean production are identified from literature survey and experts’ opinion. These include 5S, value stream mapping (VSM), just in time, single minute exchange of die, computer-integrated manufacturing, concurrent engineering, training and enterprise resource planning. ISM is used to obtain a structural relationship among these enablers of Lean. MICMAC analysis is used to identify the driving power and dependence of the variables. Further, IRP is used to rank the lean enablers with respect to key performance areas.

The ISM- and IRP-based models indicate that “training” is the most significant factor for the Lean implementation process in manufacturing sector. The MICMAC analysis also shows that “training” has the maximum driving power and the least dependence and hence has strong managerial significance. The management should place high priority on tackling this criterion. VSM occupies the top level in the ISM hierarchy, indicating that all other Lean enablers should act in unison to make VSM implementation a success.

Enablers are the building blocks for deployment of the Lean concept. To know the key enablers and relationship among them can help many organizations to develop Lean competencies. This study is perhaps among the first few that focuses on two modeling procedures based on interpretive logic, i.e. ISM and IRP. The paper provides useful insights to the Lean production implementers, consultants and researchers.