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The case study offers interesting learning possibilities and offers the following learning opportunities to the learner. assess and conduct a macro- and micro-environmental analysis, comprehend the nature of the competitive landscape and how it changes when one looks at a digital-only versus an omnichannel marketplace, examine the product mix and policy of the firm and evaluate how it delivers customer value and analyse the pros and cons of growth strategies available to a firm and arrive at a viable and actionable future business and product strategy.

The short case study presents the story of a young start-up called Country Delight. The firm began operations in 2011 and was the brainchild of Chakradhar Gade and Nitin Kaushal. The direct-to-consumer firm addressed urban consumers’ non-articulated, latent need to get “fresh and uncontaminated” milk to their doorstep. Country Delight delivered farmer-to-consumer fresh cow and buffalo milk and milk products based on a well-designed and efficient value chain where the supply chain was either wholly owned or quality monitored by the firm. The firm began operations in India’s National Capital Region and was spread across 15 metro cities. Slowly, over the years, Gade and Kaushal added more product categories.Country Delight had a subscriber base of around 500,000, and the ambitious duo wanted to double their subscriber base and reach one million subscribers by financial year 2025. The firm was looking at various paths to achieve this number. Should Country Delight expand into new geographies? Or look at adding to the existing product portfolio? Diversification into agritourism, like the Pune-based vineyard – Sula, also looked attractive to build consumer engagement. Would taking the consumer to the farmers from whom they sourced the milk and vegetables contribute additional revenue to Country Delight and their farmer-suppliers? As the firm got ready to raise another round of funding, it needed a well-articulated growth strategy that was exciting and profitable for all stakeholders.

This case study presents the dilemma entrepreneurs face as they look at the next phase of growth. Thus, this case study serves as a learning opportunity for a graduate-level course in management and as a sounding board for those who aspire to enter the start-up space. Though this case study has the potential to illustrate basic concepts such as value chain and macro- and micro-environment analysis, the protagonist’s dilemma and the problem statement make it apt for integrated discussions that are critical in advanced electives in marketing management.

Teaching notes are available for educators only.

CSS 8: Marketing.

The purpose of this paper is to investigate how absorptive capacity mediates the relationship between ambidextrous organizational learning and performance among small and medium-sized enterprises (SMEs).

Based on the resource-based view (RBV) and the dynamic capability approach, this paper uses the resource-capability-performance framework to construct the theoretical model of this study and tests the theoretical model with the questionnaire survey data of 189 SMEs in mainland China.

Ambidextrous organizational learning has different effects on SMEs' performance in terms of survival performance and growth performance. Both exploitative learning and exploratory learning have positive effects on absorptive capacity, and absorptive capacity has positive influences on both the survival performance and growth performance of SMEs. Absorptive capacity plays different mediating roles in the relationships between ambidextrous organizational learning and SMEs' performance: absorptive capacity plays a partial mediating role in the relationship between exploratory learning and SME growth performance, while absorptive capacity plays complete mediating roles in other relationships.

Managers must stress the use of exploratory learning in order to promote SMEs' growth performance. However, to foster both absorptive capacity and SME performance in terms of survival and growth, managers must pay more attention to take advantage of ambidextrous organizational learning. Government as policymakers should create a favorable environment that enable SMEs to benefit much more from the deployment of ambidextrous organizational learning and absorptive capacity.

To the best of authors’ knowledge, this study is the first to theorize and test the mediating role of absorptive capacity in the linkage between ambidextrous organizational learning and SME performance in terms of survival and growth. Additionally, this study also is the first to provide empirical support for the impact of ambidextrous organizational learning on absorptive capacity among SMEs.

This paper aims to understand the spatiotemporal influence of metro rail connectivity on housing prices in surrounding areas. The study assesses the average annual price shift for apartments around metro stations in Delhi during the previous decade, specifically from 2010 to 2019. The authors examine the spatiotemporal extents to which housing prices are determined by the prominence of metro stations and spatial development around metro stations.

The authors perform the cross-tabulation analysis to calculate chi-square values to test the hypotheses concerning the responsiveness of the housing market in Delhi to the number of locational variables in the areas connected with the mass public transportation system.

The empirical findings verify the existence of a housing market overvaluation in Delhi around metro stations until 2013, which was eventually re-adjusted after 2014. The key findings of the study suggest the role of location variables concerning metro rails in the shooting up of the housing prices in the city. In addition, the research establishes the association of annual housing price shifts to the metro rails in the short-term, mid-term and long-term in conjunction with the distance from the metro station.

In the market, the prices are often overvalued by real estate agents due to better connectivity to the metro stations. The overvaluation eventually causes massive downfalls in housing markets and rollouts as a risk for the investors. However, the effect of mass transportation on housing prices is mixed in nature, limited to a certain extent only and not as influential as frequently portrayed by the market forces. This effect loses colour with time.

This study aims to identify leather type and authenticity through optical coherence tomography.

Optical coherence tomography images taken from genuine and faux leather samples were used to create an image dataset, and automated machine learning algorithms were also used to distinguish leather types.

The optical coherence tomography scan results in a different image based on leather type. This information was used to determine the leather type correctly by optical coherence tomography and automatic machine learning algorithms. Please note that this system also recognized whether the leather was genuine or synthetic. Hence, this demonstrates that optical coherence tomography and automatic machine learning can be used to distinguish leather type and determine whether it is genuine.

For the first time to the best of the authors' knowledge, spectral-domain optical coherence tomography and automated machine learning algorithms were applied to identify leather authenticity in a noncontact and non-invasive manner. Since this model runs online, it can readily be employed in automated quality monitoring systems in the leather industry. With recent technological progress, optical coherence tomography combined with automated machine learning algorithms will be used more frequently in automatic authentication and identification systems.

A flexible manufacturing system (FMS) helps improve the system’s performance, thus increasing its overall competitiveness. FMS is an essential component of Industry 4.0 (I4.0), which has revolutionized the way firms manufacture their products. This study aims to investigate the diverse focus of the research being published over the years and the direction of scholarly work in applying FMSs in business and management.

A total of 1,096 bibliometric data were extracted from the Scopus database from the years 2001 to 2021. A systematic review and bibliometric analysis were performed on the data and related articles for performance measurement and scientific mapping on the FMS themes.

Based on co-keyword, the study reveals four major themes in the FMS field: mathematical models and quantitative techniques, scheduling and optimization techniques, cellular manufacturing and decision-making in FMSs. Based on bibliometric coupling on 2018–2021 bibliometric data, four themes emerged for future research: scheduling problems in FMS, manufacturing cell formation problem, interplay of FMS with other latest technologies and I4.0 and FMS.

The originality lies in answering the following research questions: What are the most highlighting themes in FMS, and how have they evolved over the past 20 years (2001–2021)? What topics have been at the forefront of research in FMS in the past five years (2016–2021)? What are the promising avenues of research in FMS?