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Digital platforms that offer on-demand gig work, while providing work opportunities in the economy, have raised social and economic concerns. Though extensive research on regulation of the gig economy exists, the effect of economic regulations on the welfare of the workers is not well understood. In this work, this paper aims to specifically study the effect of minimum wage and leisure regulations on the unemployment rate and offered wages. This paper also analyses the effect of up-skilling of the workers on unemployment and wages.

This paper builds an agent-based model of the labour market with heterogeneous workers and online platform firms that interact to match supply and demand. This paper also interviewed online workers in the two under-studied markets in online beauty and house maintenance services in India and included salient observations in to the model. This paper further validates the model findings with the interview observations.

Extensive simulations of the model indicate that the regulator's intervention on minimum wage and leisure reduces unemployment and offers better wages/leisure in the short term. However, these cannot be sustained unless the workers upgrade their skills, thereby improving their value to the employers. This paper also corroborates the authors’ interview observations on platforms deviating on stated worker contracts by simulating the same in the model. This paper finds that when platforms deviate on their stated incentive schemes, the unemployment rate tends to increase. This paper also finds that the emergence of online platforms in an erstwhile off-line market decreases the average unemployment rate with a moderate increase in the offered wage and leisure.

In this work, the focus has been to determine the worker-platform dyadic relationship. However, this is affected by consumer-related attributes such as ratings and associated reputation systems to promote trust between different stakeholders. Examining such a triadic relationship between consumers, platform and workers is required to comprehensively address the challenges of online gig economy.

Skilling and training are critical for worker mobility across tasks and jobs, especially in the gig economy. Gig workers, in general, seek to improve their skill level through self- or platform-enabled training programmes. The workers are able to generate more revenue through the new skills and hence can improve their reservation wage as well. This in turn increases average offered wages and reduces the overall unemployment in the sector. Despite attempts to classify gig workers as formal workers by labour laws across countries, there is resistance from online platforms. This is due to increased liability and responsibility that the platforms have to incur that possible increase their costs and expenses. This study shows that regulations, such as minimum leisure or minimum wage, increase the average wage or leisure in the market and increase unemployment. However, this might be a short-term phenomenon. In the long term, the gig workers benefit by enhancing their skills to not only stay employed but also bargain for better wages and leisure. The governments can play a larger role by facilitating upskilling programmes for the gig workers.

An extensive literature survey indicates that while most of the work on gig economy regulation emphasises the social and legal aspects, this work is unique in modeling the techno-economics of gig work. Further, while most of the economic research on gig work, focuses on consumers, this work focuses on the under-researched area of worker welfare. This paper also validates the model results with findings from the interviews with gig workers.

Despite extensive investigation of the Indian software industry, knowledge about small software firms is inadequate. This knowledge is important as many developing countries are contemplating the software industry as a means of national growth along the lines that India has taken. This paper provides a descriptive analysis of small software firms in India. It shows that small software firms that are located in software clusters; quality certified; low product oriented; and slightly larger tend to be more productive than others. Small software firms are defined as firms that have fewer software employees than the national median size. The paper used firm level data available in the Indian IT Software and Services Directory 2003, whose members contribute 95% of the industry revenue.

This paper seeks to explore the processes by which the offshoring of technology development to India and China by Western and Japanese multinationals has evolved from the localization/simplification of technology for local markets to the development of advanced technology in India and China for global markets.

Case studies were developed based on 190 interviews conducted in China, India and several other countries. Respondents included multinational home country and offshore managers, as well as local entrepreneurs.

Rather than following carefully thought out corporate strategies, the offshoring of technology development by multinationals is more often incremental and driven by the ambitions and expectations of Chinese and Indian entrepreneurs and managers. Meanwhile “technology competition” policies proposed in the USA and elsewhere are not taking sufficient account of the processes by which technology development is being offshored.

Techno‐nationalistic policies designed to allow one country to win a race with others in developing and monopolizing new technologies are increasingly dysfunctional. The identification of multinationals with “home countries” continues to weaken. At the same time, technologies and technology workers are more mobile than ever before. Better policies would allow nations to seek mutual benefit through today's more globally dispersed technology development capabilities. Multinational managers in our study were not sufficiently accounting for the costs of offshoring and outsourcing technology, nor were they giving much thought to the longer term implications of their diminishing capabilities to develop or even control the development technology. More thought should be given to what aspects of technology constitute “core competencies” and which provide sustainable competitive advantage in the emerging global environment.

Agile practices are important for executing business dealings proficiently in today’s scenario, as they thrust on implicating strategies for meeting quick market requirements. These practices are noteworthy from the point of competitiveness and for fulfilling customer’s demands speedily and promptly. The purpose of this paper is to appraise agile supplier selection dilemma based on analytical hierarchy process (AHP), which accompanied grey information. The authors drafted a group of momentous agile supplier selection measures, which can be utilized by the group of industrial and manufacturing industries to measure the status of agile parameters in their partner firms. G-TOPSIS approach to handling the case of agile supplier selection problem is presented by the authors in this work.

The conception of AHP, grey theory and TOPSIS techniques is fused in this study, under the application arena of agile supply chain management (ASCM). The AHP principals are implicated in the first phase to define the priority importance weights of agile measures and, additionally, grey theory and TOPSIS principals are fused in the second phase to fabricate a significant agile supplier selection model.

A merged approach accompanying multiple measures is developed for aiding decision making and for modeling qualitative characteristics of agile arena under grey domain. The present work can be utilized to access the agile performance characteristics of the organization and can define the status of their partner suppliers. The technical guidelines of AHP and G-TOPSIS approach are explained in this study to be implicated in distinguish decision fields. An educational podium for dispensing the theoretical knowledge on supply chain management, ASCM and agility is presented in this study.

A second-level hierarchical structure is built by the authors to facilitate the managers in taking effective decision pertaining to agile measure in their organizations. The lists of qualitative characteristics are catalogued from the literature review in this study. The built model can undertake risk associated in defining the nature of agile criterions as grey concept can undertake risk associated with the system. Thus, the authors implicated G-TOPSIS approach to handling the case of agile supplier selection problem in this study. The presented hierarchical structure will capably assist the industrial and manufacturing firms to react toward random and unpredictable market requirements, along with attaining organizations goals and profits.

The textile sector struggles with cotton stickiness from honeydew contamination. It hurts agriculture and marketability. This study aims to examine how bacterial enzymes could reduce honeydew-contaminated cotton adherence in textile businesses sustainably.

Enzyme was extracted from bacteria isolated from the fermented bamboo shoots “Lung siej”. The enzyme was tested for α-glucosidase using p-nitrophenyl-α-D-glucopyranoside as a substrate. Design of experiments determined enzyme activity temperature and reaction time. Laboratory-prepared artificial honeydew was added to ginning mill cotton to show honeydew contamination. After enzyme treatment, sticky cotton was tested for microscopic examination, ultraviolet (UV), Benedict’s, Elsner colorimetric, high volume instrument (HVI) and viscosity tests.

The bacterial isolate is characterized as Lysinibacillus sp. as confirmed by 16S rRNA gene sequencing. The enzyme extracted was identified as α-glucosidase. The ideal temperature and reaction time for enzymatic activity were 32 °C and 35 min, respectively, using central composite design. The microscopic examination, UV test, Benedict’s test, Elsner colorimetric test, HVI test and viscosity test showed that bacterial enzyme treatment reduced cotton fiber adherence.

Although few patents have examined the effect of yeast enzymes, to the best of the authors’ knowledge, a bacterial enzyme is investigated for the first time to reduce the adhesion of honeydew-contaminated cotton.

The purpose of this paper is to study the drivers of service provider switching intention other than satisfaction and, additionally, analyse the moderating role of the type of service (utilitarian vs hedonic). Specifically, the authors study the effects of alternative attractiveness, post-purchase regret, anticipated regret and past switching behaviour.

A representative survey with 800 consumers of mobile phone services (utilitarian) and holiday destinations (hedonic) was carried out.

Satisfaction is not a significant antecedent of switching intention in the hedonic service and its effect is marginal in the utilitarian service. In the utilitarian service, the main predictor of switching intention is post-purchase regret, whereas in the hedonic service, the main determinants of switching intention are past switching behaviour and anticipated regret.

The main contribution of this study is the analysis of the determinants of provider switching behaviour that may explain abandonment by satisfied customers, to see if their influence is greater or smaller than that of satisfaction itself, which has been the most analysed variable. Furthermore, there are expected to be differences between utilitarian and hedonic services, an aspect which is also studied in this work.

The COVID-19 crisis has jolted the hotel landscape profoundly and sector's usual resistance to innovative efforts is gone. Ecologically innovative (green) hotels are now expected to set the benchmark in protecting the environment and mitigating human health hazards. The need for this study stems from the fact that eco-innovative (green) hotels need not only be established and promoted, but also accepted or adopted by guests. Existing studies have mostly relied on customer's pro-environmental attitude, knowledge, and a selective list of green hotel attributes in order to predict green hotel visit intentions. The objective of this study is to provide a comprehensive list of environmental and human health attributes that are likely to influence guest's decision to visit a green hotel. One of the first studies to utilize the diffusion of innovation (DOI) theory in sustainable hospitality research, this qualitative study identifies 27 key green hotel's perceived attributes. Examining the guest's expected green hotel attributes would help managers make their green efforts more effective and attract potential guests who have not yet stayed at green hotels.

Human Resource Management and Business Strategy.

Postgraduate.

The case provides a holistic perspective of organizational transformation, management of change impact on employees and leader behavior. The challenge at Govind Milk and Milk Products Pvt. Ltd. a mid-size company, in the dairy industry was to transform itself into a pan India and global company from a regional organization. The case study outlines how the organization took on the transformation journey under a strong leadership and managed change by focusing on creating a brand, implementing technology and creating a culture of meritocracy. Having made the successful transition from being a family run business to a professionally managed company and having built significant internal capacity the big question is – Can the company strive and thrive in the VUCA business environment?

To highlight the process and management of organizational change. To highlight the role of leadership in the process of organizational change. To understand how the environmental factors or the VUCA environment impacts the performance of an organization. To highlight internal capacity building as a strategy to deal with the VUCA environment.

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: 6: Human Resource Management.

The purpose of this paper is to improve the conceptual-based search by incorporating structural ontological information such as concepts and relations. Generally, Semantic-based information retrieval aims to identify relevant information based on the meanings of the query terms or on the context of the terms and the performance of semantic information retrieval is carried out through standard measures-precision and recall. Higher precision leads to the (meaningful) relevant documents obtained and lower recall leads to the less coverage of the concepts.

In this paper, the authors enhance the existing ontology-based indexing proposed by Kohler et al., by incorporating sibling information to the index. The index designed by Kohler et al., contains only super and sub-concepts from the ontology. In addition, in our approach, we focus on two tasks; query expansion and ranking of the expanded queries, to improve the efficiency of the ontology-based search. The aforementioned tasks make use of ontological concepts, and relations existing between those concepts so as to obtain semantically more relevant search results for a given query.

The proposed ontology-based indexing technique is investigated by analysing the coverage of concepts that are being populated in the index. Here, we introduce a new measure called index enhancement measure, to estimate the coverage of ontological concepts being indexed. We have evaluated the ontology-based search for the tourism domain with the tourism documents and tourism-specific ontology. The comparison of search results based on the use of ontology “with and without query expansion” is examined to estimate the efficiency of the proposed query expansion task. The ranking is compared with the ORank system to evaluate the performance of our ontology-based search. From these analyses, the ontology-based search results shows better recall when compared to the other concept-based search systems. The mean average precision of the ontology-based search is found to be 0.79 and the recall is found to be 0.65, the ORank system has the mean average precision of 0.62 and the recall is found to be 0.51, while the concept-based search has the mean average precision of 0.56 and the recall is found to be 0.42.

When the concept is not present in the domain-specific ontology, the concept cannot be indexed. When the given query term is not available in the ontology then the term-based results are retrieved.

In addition to super and sub-concepts, we incorporate the concepts present in same level (siblings) to the ontological index. The structural information from the ontology is determined for the query expansion. The ranking of the documents depends on the type of the query (single concept query, multiple concept queries and concept with relation queries) and the ontological relations that exists in the query and the documents. With this ontological structural information, the search results showed us better coverage of concepts with respect to the query.