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The purpose of this paper is to identify the key enabler for total productive maintenance (TPM) implementation in Indian small and medium enterprises (SMEs) by using graph theoretic approach (GTA). There are certain enablers for TPM implementation which helps the organization to implement it successfully. It is very essential to identify the nature and impact of these key enablers.

A large number of the enablers (27) have identified for TPM implementation in Indian SMEs from the available literature, questionnaire survey and expert opinion. These TPM enablers have categorized into six major categories.

In this research work, the intensity of identifying enablers has been calculated to show their impact or influence in TPM implementation. The value of intensity of TPM enablers shows the role or impact of individual enabler in the implementation of TPM in Indian SMEs.

This study provides an easy-to-use methodology for the practical decision makers in the manufacturing industry to improve their performance by implementing TPM in Indian SMEs. A detailed methodology has prepared to identify the enablers for TPM implementation in Indian SMEs by using GTA. This study also explains that how to check the feasibility of an organization to implement TPM in Indian SMEs successfully.

TPM is an improvement concept which holds the potential to improve manufacturing organizations, but its implementation is not easy in Indian SMEs. The reason behind the unsuccessful implementation of TPM in most of the organizations is the ignorance of impact of innumerable enablers and barriers.

The purpose of this paper is to introduce mobile maintenance a new concept of total productive maintenance (TPM) implementation practice, especially in small and medium scale enterprises (SMEs). This study tries to introduce this new concept for SMEs in SMEs to help traditional maintenance program which is already available in particular industries.

The approach is to study the role of mobile maintenance (a part of TPM program) in context of Indian industries either from small and medium scale to large scale industries through overall equipment effectiveness (OEE).

Researchers evolutes a new maintenance concept of TPM implementation practice as mobile maintenance concept in SMEs for enhancing OEE of equipments to improve competitiveness of SMEs in a globalized market. This mobile maintenance strategy can reduce major breakdowns, setup and adjustment losses and improve productivity, product quality and OEE of equipments.

In the dynamic and highly challenging environment, reliable manufacturing equipments are regarded as the major contributor to the performance and profitability of manufacturing systems. A researcher has found that some SMEs of Banmore industrial areas is also using mobile maintenance and preventive maintenance along with traditional maintenance process and getting improvements in the maintenance process as well as machine reliability and OEE of equipments. After the globalization of market, SMEs has got many opportunities to work on integration with large-scale organizations.

It will be very benefitted for the Indian SMEs. SMEs can improve machine availability and OEE by implementing this mobile maintenance concept especially in SMEs.

The purpose of this paper is to review the literature on total productive maintenance (TPM) implementation practice to present an overview of TPM implementation practices adopted by various manufacturing organizations and suggest possible gaps from researchers and practitioner’s point of view. This study tries to identify the best strategy for improving competitiveness of small and medium enterprises (SMEs) in globalized market and evaluates TPM implementation practice in SMEs.

The objective of this paper is to study the role of TPM program in context of Indian industries either from SMEs to large-scale industries. The approach has been directed toward justification of TPM implementation practice for its support to competitive manufacturing in the context of Indian manufacturing industries.

TPM implementation improves productivity and working efficiency of employees and also improves equipment effectiveness and a positive inclination toward company is registered. Therefore, equipment maintenance is an indispensable function in a manufacturing enterprise. In this highly competitive environment, manufacturing organizations should consider maintenance function as a potential source for cost savings and competitive advantage. SMEs must be considered as an engine for economic growth all over the world (Singh et al., 2008). A total of 148 papers related to TPM implementation in large-scale industries and SMEs were collected, analyzed and classified on the basis of their applications, broadly into large industry and SMEs and further divided into Indian and Non-Indian, then case study, implementation, model, literature review, maintenance, service, etc. This classification has clearly shows that SMEs are in a need to adopt TPM implementation practice to compete in this global market and changing requirements of large industries. Maintenance is an indispensable function in a manufacturing enterprise. In this highly competitive environment, manufacturing organizations must be considered maintenance function as a potential source for cost savings and competitive advantage. Singh et al. (2008) have concluded that SMEs must be considered as an engine for economic growth of all over the world. Following are the objectives of this study: to suggest a classification of available literature on TPM implementation; to identify the need of TPM implementation in SMEs; to identify critical observations on each category of classification; to identify the potential of SMEs in India; to identify emerging trends of TPM implementation in India; to suggest directions for future researchers in the field of TPM implementation on the basis of above mention points; and to consolidate all available literature on TPM implementation practice.

The challenges of stiff competition and the drive for profits are forcing the organizations to implement various productivity improvement efforts to meet the challenges posed by ever-changing market demands. In the dynamic and highly challenging environment, reliable manufacturing equipment is regarded as the major contributor to the performance and profitability of manufacturing systems.

In this dynamic world, importance of SMEs in the growth of the nation needs more attention of researchers and industrialists. After the globalization of market, SMEs have got many opportunities to work in integration with large-scale organizations. All the organizations from SMEs to large-scale industries can adopt effective and efficient maintenance strategies such as condition-based maintenance, reliability-centered maintenance and TPM over the traditional firefighting reactive maintenance approaches (Sharma et al., 2005).

In our view, this paper clearly identifies implications for research which will be useful for society. The gap discussed by authors needs to be addressed by future researchers.

This implementation strategy can help to save huge amounts of time, money and other useful resources in dealing with reliability, availability, maintainability and performance issues. On the basis of available literature, it can be understood that SMEs should change their maintenance strategies to cope up with global competition so that a lot of resources can be utilized in a better direction.

This research aims to investigate critical success factors, barriers and initiatives of total productive maintenance (TPM) implementation in selected manufacturing industries in Addis Ababa, Ethiopia.

This study built and looked into a conceptual research framework. The potential barriers and success factors to TPM implementation have been highlighted. The primary study techniques used to collect relevant data were a closed-ended questionnaire and semi-structured interview questions. With the use of SPSS version 23 and SmartPLS 3.0 software, the data were examined using descriptive statistics and the inferential Partial Least Square Structural Equation Modeling (PLS-SEM) techniques.

According to the results of descriptive statistics and multivariate analysis using PLS-SEM, the case manufacturing industries' TPM implementation initiative is in its infancy; break down maintenance is the most widely used maintenance policy; top managers are not dedicated to the implementation of TPM; and there are TPM pillars that have been weakly and strongly addressed by the case manufacturing companies.

The small sample size is a limitation to this study. It is therefore challenging to extrapolate the research findings to other industries. The only manufacturing KPI utilized in this study is overall equipment effectiveness (OEE). It is possible to add more parameters to the manufacturing performance measurement KPI. The relationships between TPM and other lean production methods may differ from those observed in this cross-sectional study. Longitudinal experimental studies and in-depth analyses of TPM implementations may shed further light on this.

Defining crucial success factors and barriers to TPM adoption, as well as identifying the weak and strong TPM pillars, will help companies in allocating their scarce resources exclusively to the most important areas. TPM is not a quick solution. It necessitates a change in both the company's and employees' attitude and their values, which takes time to bring about. Hence, it entails a long-term planning. The commitment of top managers is very important in the initiatives of TPM implementation.

This study is unique in that, it uses a new conceptual research model and the PLS-SEM technique to analyze relationships between TPM pillars and OEE in depth.

There are two theoretical concepts that can be taught in this case.The new approach to teaching entrepreneurship is termed “lean start-up” and “hypothesis-driven entrepreneurship.” The business model canvas is a core tool of this approach. This framework defines nine key components of a successful business strategy. These components include defining value propositions; identifying customer segments; identifying channels; maintaining customer relationships; defining key activities, key resources and key partners; understanding the revenue model of the business; and the organization’s cost structure. This is considered to be a rigorous approach to learning about and developing a new venture.The other theoretical approach that can be discussed through this case is the link between uncertainty and entrepreneurial growth. These theories associate the willingness of entrepreneurs to bear the perceived uncertainty associated with entrepreneurial acts as representative of the belief-desire model. There is a need for entrepreneurs to experiment and search for alternative paths forward in order to counter this uncertainty. Systematic search processes to discover relevant information will strengthen this process.

This case is based on primary data collected through interviews with company personnel. The company consented freely to the use of their data in the case. The authors have no connection with the company. The four student coauthors had previously pursued an internship with the company and had worked on the machine learning analysis part.The two faculty coauthors in the case contacted the company after the internship and discussed the opportunity to write the case on the company. One of the faculty then interviewed key personnel in the company, including one of the co-founders.

Xoxoday is a technology company that provides employee rewards and corporate gifting to its customers. The company was started by Sumit Khandelwal, Manoj Agarwal, Abhishek Kumar and Kushal Agarwal. In 2018, the company reinvented itself as an experiential gifting company.The company faced some challenges during the lockdowns imposed due to COVID-19. Khandelwal knew that they had to try something new to achieve higher growth in the future. He wondered if higher usage of technology was the solution. It was necessary for them to carve a new path in these times.

This case study can be used at the undergraduate level in courses relating to entrepreneurship strategy and business models for entrepreneurs.The case can be used to highlight the dilemmas faced by entrepreneurs due to unforeseen crises. This case is relevant for classes that will discuss growth crises and out-of-the-box solutions for unprecedented crisis situations.

Transaction monitoring system set up by financial institutions is one of the most used ways to track money laundering and terrorist financing activities. While being effective to a large extent, the system generates very high false positives. With evolving patterns of financial transactions, it also needs effective mechanism for scenario fine-tuning. The purpose of this paper is to highlight quantitative method for optimizing scenarios in money laundering context. While anomaly detection and unsupervised learning can identify huge patterns of false negatives, that can reveal new patterns, for existing scenarios, business generally rely on judgment/data analysis-based threshold finetuning of existing scenario. The objective of such exercises is productivity rate enhancement.

In this paper, the authors propose an approach called linear/non-linear optimization on threshold finetuning. This traditional operations research technique has been often used for many optimization problems. Current problem of threshold finetuning for scenario has two key features that warrant linear optimization. First, scenario-based suspicious transaction reporting (STR) cases and overall customer level catch rate has a very high overlap, i.e. more than one scenario captures same customer with different degree of abnormal behavior. This implies that scenarios can be better coordinated to catch more non-overlapping customers. Second, different customer segments have differing degree of transaction behavior; hence, segmenting and then reducing slack (redundant catch of suspect) can result in better productivity rate (defined as productive alerts divided by total alerts) in a money laundering context.

Theresults show that by implementing the optimization technique, the productivity rate can be improved. This is done through two drivers. First, the team gets to know the best possible combination of threshold across scenarios for maximizing the STR observations better coverage of STR – fine-tuned thresholds are able to better cover the suspected transactions as compared to traditional approaches. Second, there is reduction of redundancy/slack margins on thresholds, thereby improving the overall productivity rate. The experiments focused on six scenario combinations, resulted in reduction of 5.4% of alerts and 1.6% of unique customers for same number of STR capture.

The authors propose an approach called linear/non-linear optimization on threshold finetuning, as very little work is done on optimizing scenarios itself, which is the most widely used practice to monitor enterprise-wide anti-money laundering solutions. This proves that by adding a layer of mathematical optimization, financial institutions can additionally save few million dollars, without compromising on their STR capture capability. This hopefully will go a long way in leveraging artificial intelligence for further making financial institutions more efficient in controlling financial crimes and save some hard-earned dollars.

Strategic Marketing, Marketing Management, Services Marketing.

MBA and Executive MBA.

The case talks about the inception and growth of OYO Rooms, a company that originally started as ORAVEL Stays Ltd. in 2012, as a platform for booking budget and premium accommodations, but graduated to become OYO Rooms, an online aggregator of hotels, with a unique business model of “managing the partial inventory of rooms” in hotels and offering a proposition of affordable, consistent, quality experience to business, leisure and pilgrim travellers. The company received rounds of funding from Greenoaks Capital, Lightspeed Ventures, Sequoia Capital and DSG Consumer Partners. Moreover, unlike its competitors, OYO adapted itself to the fast-changing consumer preference and grew at an enviable pace and by 2016, was present across 190 cities through a network of 6,500 hotels. However, OYO Rooms had to face a multitude of challenges both from the consumer and hotel owners’ ends, primarily service quality concerns from the customers and majorly concerns out of payment irregularities or non-abidance to written contracts from the hoteliers’ end. The dissatisfaction levels increased to an extent that experts started raising questions on the viability of the business. OYO was growing at an aggressive rate but breakeven point was yet to be achieved. Moreover, growing dissatisfaction and switching amongst its customers as well as hoteliers threatened the very existence of the model. The case allows the students to critically analyse the strategies of OYO for deliberation on whether the business model was sustainable in the long run. It also encourages the students to deliberate on the possible growth strategies for OYO as also on the service recovery strategies for OYO.

The case has been positioned around the following modules: industry analysis; value of a two-sided business model to both parties; sustainability of a unique business model, against the challenges that it faces; applying the VRIO framework (resource-based view); complaint handling and service recovery strategies; applying the Ansoff’s grid for possible growth options.

Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

CSS 11: Strategy.

Children are the most vulnerable group owing to long lasting impact of the violation of human rights in term of proper nutrition and their right to live. The purpose of this paper is to assess the risk of child mortality associated with size of child at birth and mother’s anemia level in northern India.

The data were used from 2015–2016 National Family Health Survey (NFHS). The participants (n = 41,412) were children aged under-five years from north Indian state of Uttar Pradesh. The main outcome measure was child deaths defined by under-five mortality. The univariate, bivariate and multivariate analyses were used in data analysis. Kaplan–Meier analyses, Log-rank tests and Cox’s regression analyses were performed to fulfill the objective of the study.

There were a total of 2,835 deaths out of 41,412 births in the past five years preceding the survey period. Children of very small size at birth were significantly two and half times more likely to die than children of average size at birth. The estimated adjusted hazard ratio indicated that the children of severely anemic mothers were significantly 1.5 times more likely to die compared to children of not anemic mothers. Size of child at birth, mother’s anemia level, mother’s age at time of her first birth, wealth index and mother’s education were significantly associated with the under-five mortality in northern India.

The limitation of this study is recall errors arising from the dates of birth and death given by women interviewed in the survey were minimized by restricting the analyses to births within the five-year period preceding the survey.

This study advocates the promotion of comprehensive prevention strategies through appropriate institutional mechanism would be the best intervention or adaptive mechanism to reduce the adverse impact of size of child at birth, mother’s anemia level on under-five mortality in Uttar Pradesh, India.

This research is original. This study enjoys a unique importance by exploring effect of size of child at birth and mother’s anemia on child survival in developing countries like India.

The purpose of this paper is to discuss how the rush of technological change will consolidate the worldwide reach of the internet with more capacity, specifically to control the physical world, including the machines, industrial facilities and frameworks that characterize cutting-edge technology.

The data were collected from 203 respondents predominantly from emerging economies, specifically India and SEA. Most of the participants are working professionals. Structural equation modelling was used to analyze data, as it is a popular statistical technique because of its ability to model selected independent variables and take into account all possible forms of measurement error to test an entire theory.

The Industrial Internet of Things (IIOT) platform comprises four fundamental capabilities: connectivity, big data, advanced analytics and application development. The IIOT has the potential to provide a high level of synergies between the 4 Ms of manufacturing, namely, man, machine, material and method.

The collected data are predominately from India and SEA (close to 75 per cent), while contributions from other regions are comparatively less, so the findings cannot be generalized to the global context.

It is in the interest of service providers to collaborate and provide a universal solution to retain legacy systems to minimize the investment and reduce the security threat, which could boost IIOT adoption while ensuring that manufacturers are able to leverage this new technology efficiently.

The framework obtained has good quality of validity and reliability indicators. Thus, an alternative framework has been added to customer expectation which is currently a popular topic in the technological changes.

Deepfakes are fabricated content created by replacing an original image or video with someone else. Deepfakes have recently become commonplace in politics, posing serious challenges to democratic integrity. The advancement of AI-enabled technology and machine learning has made creating synthetic videos relatively easy. This study explores the role of political brand hate and individual moral consciousness in influencing electorates' intention to share political deepfake content.

The study creates and uses a fictional deepfake video to test the proposed model. Data are collected from N = 310 respondents in India and tested using partial least square–structural equation modelling (PLS-SEM) with SmartPLS v3.

The findings support that ideological incompatibility with the political party leads to political brand hate, positively affecting the electorates' intention to share political deepfake videos. This effect is partially mediated by users' reduced intention to verify political deepfake videos. In addition, it is observed that individual moral consciousness positively moderates the effect of political brand hate on the intention to share political deepfake videos. Intention to share political deepfake videos thus becomes a motive to seek revenge on the hated party, an expression of an individual's ideological hate and a means to preserve one's moral self-concept and strengthen their ideologies and moral beliefs.

The study expands the growing discussion about disseminating political deepfake videos using the theoretical lens of the negative consumer-brand relationship. It validates the effect of political brand hate on irrational behavior that is intended to cause harm to the hated party. Further, it provides a novel perspective that individual moral consciousness may fuel the haters' desire to engage in anti-branding behavior. Political ideological incompatibility reflects ethical reasons for brand hate. Therefore, hate among individuals with high moral consciousness serves to preserve their moral self.