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Need for preventive health care: To comprehend the contribution of preventive health care in improving the health quotient. Sri Sathya Sai Sanjeevani Hospital (SSSSH) and its initiative is an apt example of the wonder which preventive care can bring in the context of rural health. Community participation: The case can be instrumental in showing the pathway to encourage community involvement in mainstream health by promoting the holistic model of SSSSH that understands mothers and children's health profile and needs, especially in the unreached rural segments of an emerging economy like India. Importance of healthy childhood: World Health Organization (WHO) promotes the school health programme to prevent health risks among children by inculcating healthy behaviours during childhood. The successful SSSSH model proves that it is implementable by integrating comprehensive health education modules in the existing institutions for medical care.

The challenge of a healthy childhood is inadequate availability and accessibility of quality care. Non-awareness of the parents is also a significant reason for the children who miss the benefit of a happy childhood. While much is planned by the Government and some part of it being executed, this case highlights the effectiveness of the maternal and child health programme executed by the Sri Sathya Sai Sanjeevani Hospital (SSSSH). This initiative fulfills the dire need of ensuring the preventive healthcare component leading to safe motherhood and safe birth of healthy children. Further, the case is also the culmination of pin-pointed innovative awareness activities such as school health screening and the Divine Mother and Child Health Program (DMCHP). It opens up the discussion on the current model of health care followed by SSSSH, Raipur, and its impact in the local areas to decide on its expansion across the country for nationwide implementation.

Bachelors in Business Administration, MBA, Executive MBA, Post Graduate Diploma in Healthcare Management

Teaching notes are available for educators only.

CSS 2: Built Environment.

The purpose of this paper is to understand the dimensions of the e-fulfillment process and its influence on customers in pure e-tailing; to classify the pertinent literature that has evolved over time addressing relevant managerial issues; and to identify the gaps between the practices prevalent in the e-fulfillment and those suggested by academicians to develop insights for future research.

A critical systemic literature review approach was used for the study with quantitative and qualitative analysis.

The authors identified seven dimensions of e-fulfillment in the literature on pure e-tailing: e-business quality, product quality, pricing, availability, timeliness, condition and ease of return and explored its linkages with shopping satisfaction and repurchase intention of customers in e-tailing.

The study was skewed toward an empirical approach. The study does not include many of the analytical models in this space.

This study helps e-tailers, academicians and practitioners understand critical dimensions of e-fulfillment and its influence on customers in the pure e-tailing setting in order to design customer-centric e-fulfillment architecture.

The study identified seven dimensions of e-fulfillment in the literature and explored its influence on shopping satisfaction and repurchase intention of customers in pure e-tailing. This is the first compilation of standalone/isolated studies available in the literature to provide e-tailers and academicians meaningful insights into e-fulfillment in the pure e-tailing setting.

The learning outcomes of this case study are as follows: It presents an opportunity for the instructors to introduce the concept of decision-making on matters involving risk (like scaling the business) using in-depth market research techniques. The case’s central idea is to make the students understand the growth of the online service delivery model, with a specific example of home-cooked food that also improves social welfare. It is expected to provide the participants with an opportunity to understand the decision-making by the leaders in newly established companies. It enables future managers to analyze a venture’s pros and cons before deciding to expand.

Chef Junction is an online food delivery platform that allows customers to order hygienic home-cooked food prepared by handpicked home chefs in Bhubaneswar. This city in eastern India is one of the fastest-growing metros, is regarded as a study hub, and provides ample employment opportunities making it one of the sought-after destinations for the migrant youth population. The idea behind Chef Junction is to cater to the healthy food needs of the young by utilizing the culinary productivity of the home cooks, empowering the latter by opening up an extra source of income. These chefs prepare delicious healthy food, usually not listed for sale with online food delivery apps. Chef Junction earned revenues by adding an order-dependent commission on the price quoted by chefs and accepting a flat delivery charge from the customers. This offer was very lucrative for home chefs who could join the platform with zero investment and flexible working hours. The customer’s pockets were also handled when several offers and discounts were rolled out through an attractive pricing strategy. Chef Junction expected to improve its patrons’ health quotient by ensuring the nutrition of the home-cooked food, thus contributing to social welfare. With food being delivered from home to home amalgamated with social welfare and empowerment of home chefs, especially women, this case study is an apt example of a sustainable work-from-home model that has proved effective in crisis times. The pertinent question is: “How feasibly can CJ’s business model grow towards an expansion as the demand increases?”

This case study has been prepared keeping in mind the teaching pedagogy for graduate and postgraduate management programs in strategic management, operations research, entrepreneurship and marketing management. It is also expected to be useful for training courses such as management development programs, faculty development programs and executive programs, in discussing service operations in general and online delivery logistics, in particular for working executives and industry practitioners.

Teaching notes are available for educators only.

CSS 3: Entrepreneurship.

Online food delivery (OFD) has witnessed momentous consumer adoption in the past few years, and COVID-19, if anything, is only accelerating its growth. This paper captures numerous intricate issues arising from the complex relationship among the stakeholders because of the enhanced scale of the OFD business. The purpose of this paper is to highlight publication trends in OFD and identify potential future research themes.

The authors conducted a tri-method study – systematic literature review, bibliometric and thematic content analysis – of 43 articles on OFD published in 24 journals from 2015 to 2021 (March). The authors used VOSviewer to perform citation analysis.

Systematic literature review of the existing OFD research resulted in six potential research themes. Further, thematic content analysis synthesized and categorized the literature into four knowledge clusters, namely, (i) digital mediation in OFD, (ii) dynamic OFD operations, (iii) OFD adoption by consumers and (iv) risk and trust issues in OFD. The authors also present the emerging trends in terms of the most influential articles, authors and journals.

This paper captures the different facets of interactions among various OFD stakeholders and highlights the intricate issues and challenges that require immediate attention from researchers and practitioners.

This is one of the few studies to synthesize OFD literature that sheds light on unexplored aspects of complex relationships among OFD stakeholders through four clusters and six research themes through a conceptual framework.

Pay-what-you-want (PWYW) is a pricing strategy implemented in a variety of settings like supermarkets and museums, in which consumers determine the price they are willing to pay for a product or service based on their perceived utility. The authors propose an analytical model to investigate the impact of PWYW delivery pricing on the online food delivery (OFD) platforms.

Using a game-theoretic model, the authors characterize the equilibrium as a function of the platform's average delivery cost and the consumer's social preferences parameters like fairness and reciprocity. The authors derive the parametric conditions under which PWYW generates higher profits for the platform compared to the traditional pay-as-asked delivery pricing.

For the PWYW strategy to be profitable, the average delivery cost to the platform should be low. Therefore, OFD platform managers should focus on reducing delivery costs. The authors also identify the feasible region in which the platform managers need to maintain the consumer's social preferences.

Under PWYW, the authors recommend that the platform managers impose a minimum delivery fee which consumers can use as a benchmark to minimize zero delivery fee payments and consumers' free-riding tendencies simultaneously. This allows OFD platforms to extract online orders from highly price-conscious consumers.

This is one of the first studies to explore the innovative application of PWYW to a particular segment of delivery pricing in OFD platforms. The authors establish that the overall consumer surplus and social welfare are higher under the PWYW strategy, forming a solid ground for its implementation in OFD platforms.

Due to the ever increasing concern toward sustainability, suppliers nowadays are evaluated on the basis of environmental performances. The data on supplier’s performance are not always available in quantitative form and evaluating supplier on the basis of qualitative data is a challenging task. The purpose of this paper is to develop a framework for the selection of suppliers by evaluating them on the basis of both quantitative and qualitative data.

Literature on sustainability, green supply chain and lean practices related to supplier selection is critically reviewed. Based on this, a two phase fuzzy goal programming approach integrating hyperbolic membership function is proposed to solve the complex supplier selection problem.

Results obtained through the proposed approach are compared to the traditional models (Jadidi et al., 2014; Ozkok and Tiryaki, 2011; Zimmermann, 1978) of supplier selection and were found to be optimal as it achieves higher aspiration level.

The proposed model is adaptive to solve real world problems of supplier selection as all criteria do not possess the same weights, so the managers can change the criteria and their weights according to their requirement.

This paper provides the decision makers a robust framework to evaluate and select sustainable supplier based on both quantitative and qualitative data. The results obtained through the proposed model achieve greater satisfaction level as compared to those achieved by traditional methods.

The case presents a customer's experience during the purchase of a pair of shoes in an upmarket retail outlet of Bharat Footwear Limited (BFL), in Ahmedabad, wherein he was offered a discount coupon meant for shareholders, at a shared consideration of 60 (buyer) and 40 (agent). The customer needs to decide on the acceptance or otherwise of the deal. Adequate data is provided to discuss this central issue in a business context along with an estimate of the secondary market of discount coupons. The analysis of the case leads to a debate on whether the discount policy should be continued or otherwise. While several sharing arrangements for the discount amount are considered, the key to the situation is not such arrangements but a robust system in dispensing these coupons.

The assorted piece-wise retail orders in a cosmetics warehouse are fulfilled through a separate fast-picking area called Forward Buffer (FB). This study determines “just-right” size of FB to ensure desired Customer Service Level (CSL) at least storage wastages. It also investigates the impact of FB capacity and demand variations on FB leanness.

A Value Stream Mapping (VSM) tool is applied to analyse the warehouse activities and mathematical model is implemented in MATLAB to quantify the leanness at desired CSL. A comprehensive framework is developed to determine lean FB buffer size for a Retail Distribution Centre (RDC) of a cosmetics industry.

The CSL increases monotonically; however, the results concerning spent efforts towards CSL improvement gets diminished with raised demand variances. The desired CSL can be achieved at least FB capacity and fewer Storage Waste (SW) as it shifts towards more lean system regime. It is not possible to improve Value Added (VA) time beyond certain constraints and therefore, it is recommended to reduce Non-Value Added (NVA) order processing activities to improve leanness.

This study determines “just-right” capacity and investigates the impact of buffer and demand variations on leanness. It helps managers to analyse warehouse processes and design customized distribution policies in food, beverage and retail grocery warehouse.

Proposed buffering model offers customized strategies beyond pre-set CSL by varying it dynamically to reduce wastages. The mathematical model deriving lean sizing and mitigation guidelines are constructive development for managers.

This research provides an inventive approach of VSM model and Mathematical algorithm endorsing lean thinking to design effective buffering policies in a forward warehouse.

Despite the current progress in realizing how Big Data Analytics can considerably enhance the Sustainable Manufacturing Supply Chain (SMSC), there is a major gap in the storyline relating factors of Big Data operations in managing information and trust among several operations of SMSC. This study attempts to fill this gap by studying the key enablers of using Big Data in SMSC operations obtained from the internet of Things (IoT) devices, group behavior parameters, social networks and ecosystem framework.

Adaptive Prospects (Improving SC performance, combating counterfeits, Productivity, Transparency, Security and Safety, Asset Management and Communication) are the constructs that this research first conceptualizes, defines and then evaluates in studying Big Data Analytics based operations in SMSC considering best worst method (BWM) technique.

To begin, two situations are explored one with Big Data Analytics and the other without are addressed using empirical studies. Second, Big Data deployment in addressing MSC barriers and synergistic role in achieving the goals of SMSC is analyzed. The study identifies lesser encounters of barriers and higher benefits of big data analytics in the SMSC scenario.

The research outcome revealed that to handle operations efficiently a 360-degree view of suppliers, distributors and logistics providers' information and trust is essential.

In the Post-COVID scenario, the supply chain practitioners may use the supply chain partner's data to develop resiliency and achieve sustainability.

The unique value that this study adds to the research is, it links the data, trust and sustainability aspects of the Manufacturing Supply Chain (MSC).

The contemporary e-tailing marketplace insists that distribution centers are playing the roles of both wholesalers and retailers which require different storage-handling load sizes due to different product variants. To fulfill piecewise retail orders, a separate small size-fast pick area is design called “forward buffer” wherein pallets are allocated from reserve area. Due to non-uniform pallets, the static allocation policy diminishes forward space utilization and also, more than practically required buffer size has been identified as wastage. Thus, dynamic storage allocation policy is required to design for reducing storage wastage and improving throughput considering non-uniform unit load sizes. The purpose of this paper is to model such policy and develop an e-decision support system assisting enterprise practitioners with real-time decision making.

The research method is developed as a dynamic storage allocation policy and mathematical modeled as knapsack-based heuristics. The execution procedure of policy is explained as an example and tested with case-specific data. The developed model is implemented as a web-based support system and tested with rational data instances, as well as overcoming prejudices against single case findings.

The provided model considers variable size storage-handling unit loads and recommends number of pallets allocations in forward area reducing storage wastes. The algorithm searches and suggests the “just-right” amount of allocations for each product balancing existing forward capacity. It also helps to determine “lean buffer” size for forward area ensuring desired throughput. Sensitivity and buffer performance analysis is carried out for Poisson distributed data sets followed by research synthesis.

Warehouse practitioners can use this model ensuring a desired throughput level with least forward storage wastages. The model driven e-decision support system (DSS) helps for effective real-time decision making under complicated business scenarios wherein products are having different physical dimensions. It assists the researchers who would like to explore the emerging field of “lean” adoption in enterprise information and retail-distribution management.

The paper provides an inventive approach endorsing lean thinking in storage allocation policy design for a forward-reserve model. Also, the developed methodology incorporating features of e-DSS along with quantitative modeling is an inimitable research contribution justifying rational data support.