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The purpose of this paper is to achieve intelligent superstore site selection. Yonghui Superstores partnered with Cardinal Operations to incorporate a tremendous amount of site-related information (e.g. points of interest, population density and features, distribution of competitors, transportation, commercial ecosystem, existing own-store network) into its store site optimization.

This paper showcases the integration of regression, optimization and machine learning approaches in site selection, which has proven practical and effective.

The result was the development of the “Yonghui Intelligent Site Selection System” that includes three modules: business district scoring, intelligent site engine and precision sales forecasting. The application of this system helps to significantly reduce the labor force required to visit and investigate all potential sites, circumvent the pitfalls associated with possibly biased experience or intuition-based decision making and achieve the same population coverage as competitors while needing only half the number of stores as its competitors.

To our knowledge, this project is among the first to integrate regression, optimization and machine learning approaches in site selection. There is innovation in optimization techniques.

Large supermarkets, chain stores and enterprises with large-scale warehousing put forward higher standards and requirements for the automation and informatization of warehouses. As one of the fast-growing commercial supermarkets in China, the traditional warehouse management mode has restricted the rapid development of Yonghui Superstores to a certain extent. The purpose of this paper is to find out how the existing warehouse mode can be changed and to solve the existing problems of warehouse management of Yonghui Superstores.

This research puts forward construction of warehouse center, which is based on radio frequency identification (RFID) and sensor technology, then designs the model for receiving, storage, operations management, distribution and outbound to solve the existing problems of warehouse management of Yonghui Superstores.

What technologies should be adopted to meet storage requirements? How to monitor the storage environment in real time and improve the operation and management level of the warehouse? This study found that building a warehouse center based on RFID and sensor technology was a good solution.

The Yonghui Superstores warehouse center model lacks corresponding simulation experiments, and the investment and income are difficult to estimate quantitatively.

This paper has designed and discussed the warehouse center model based on RFID and sensor technology, which provides a few references for the actual investment and construction of a warehouse center. In addition, the warehouse center model has strong generalized applicability and could be widely used in various enterprises.

The warehouse center could improve the warehouse management level of Yonghui Superstores and change the traditional warehouse management mode. To some extent, it improves the enterprise flexibility of the market, which will be of great significance to improve business efficiency and enhance brand image and competitiveness.

This study takes Yonghui Superstores as a case to analyze the problems of warehousing management in detail and then designs a warehouse center based on RFID and sensor technology. The study discusses the location and distribution, software and hardware selection, benefits evaluation, significances and return on investment, which makes the warehouse center model versatile, technically feasible and economically applicable.

The challenge of sustaining growth seems to be getting steeper and steeper. This Masterclass provides context for two recent books that have valuable insights to offer to company leaders and strategists on how to build resilience and sustain growth in increasingly dynamic and uncertain global competitive markets.

In The Founder’s Mentality: How to Overcome the Predictable Crises of Growth (2016), well-known Bain strategy consultants, Chris Zook and James Allen offer a strategy for consciously embedding “the founder’s mentality” into the culture of young firms as they scale or rediscovering it in mature firms that might be stalling and losing their way. For strategy and innovation guru, Vijay Govindarajan, sustaining growth increasingly requires being able to pursue simultaneously two very different types of activity and mindset – exploiting a legacy business while exploring new business opportunities. He offers a very practical framework for approaching this challenge in The Three Box Solution: A Strategy for Leading Innovation.

The “founder’s mentality” refers to “a collection of specific behaviors and attitudes best exemplified by the traits of great founders that if properly cultivated in the rest of the organization, can lead more reliably to sustainable growth.” Some young firms fail to establish a founder’s mentality from the outset, while many mature founder-led companies come to lose their sense of insurgency and other key founder’s mentality traits over time. “Just about every company, at any stage in its life, can benefit from the attitudes and behaviors that make up the founder’s mentality.”

Govindarajan argues that “asking what assumptions must be true for this idea to be highly profitable” and testing the most critical of these “as early and as inexpensively as possible” is ‘the best way to reveal an ill-conceived project.

The two books, taken together, provide a wealth of insight for leaders seeking to diagnose their firm’s growth problems and looking for potential solutions for reviving innovation and growth.

The tech giants Alibaba and Tencent compete on many fronts. This case focuses on three areas where they have competed very hard: new retailing, mobile payment, and ride-hailing. At the beginning of 2018, Alibaba and Tencent were gathering retail investments in bids to battle each other for shoppers' digital wallets. Key to the battle is China's mobile payment market, worth more than 200 trillion RMB, where Alibaba and Tencent are going head to head. The giants are not only directly competing in the payment platform area but also extensively fighting in other areas, such as ride-hailing, where they invested in and supported Didi and Kuaidi, respectively. To enhance understanding, this case also briefly goes through the history of the two giants. The purposes, methods, and consequences of their platform competition deserve an in-depth discussion

Following are the learning outcomes: to understand how the tools and frameworks of strategic analysis can be applied to understand the evolution of value creation and capture in the FMCG industry; to analyze the core competencies of a company and understand their relevance in this fast-changing industry; to understand how to evaluate the pros and cons of a certain strategy and business model; and to develop strategic recommendations.

The case series traces the developments in China’s FMCG industry from the early 2010s to 2017, in general, and the efforts of Beijing WinChannel Software Technology Co., Ltd. (WinChannel) and its affiliated company, Huixiadan, in their attempt to apply new digital technologies to transform the traditional trade channel, in particular. The decision point of Case A, in early 2015, is how WinChannel can help improve the reach and efficiency of the traditional trade channel and wonders if the emerging online/mobile B2B FMCG platforms are the right solution for the increasingly digitized FMCG retail industry in China. The decision point of Case B, at the end of 2017, is how could Huixiadan’s business model be sustainable and what it should do to withstand the competitive threats even as it tries to exploit opportunities in the traditional FMCG industry in China.

It can be used with MBAs, EMBAs and senior executives.

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.

The authors seek to crack the model of new retail by outlining the unique business model known as community-based omni-channel and data-enabled ecosystem.

The study’s analyses of Hema cases and other examples reveal a new omni-channel model, a community-based and data-enabled ecosystem model.

The ecosystem targets local customers within a limited geographical range. It is also data-enabled and effectively leverages large-scale data on consumers, store operations, supply chains and logistics to ensure the smooth functioning of the ecosystem.

The authors hope the typology brings new insights to the development of omni-channel retail.

This paper aims to theoretically investigate an online company’s optimal decision on its offline expansion strategy. In the past five years, many large online retailers and internet-based companies such as Amazon, Google, Alibaba, Tencent and JD.com have expanded their offline market but it was observed that they adopted different expansion strategies. Specifically, some of them expand the offline market by acquiring offline retailers, while some do so by purchasing a portion of offline retailer’s stake. This difference leads to a quite different structure in post-expansion market, having an impact on profit, consumer surplus and social welfare. The goal of this paper is to model such expansion strategies in a general way and complete studies on profits and welfare.

By constructing a Salop model with two offline retailers and one online company, this paper analyzes the case where the online company can expand its offline market by either acquiring or jointing (e.g. stakeholding) with one offline retailer. The former strategy (named Strategy A) allows the online company to fully control and capture residual claims of the offline retailer. With the adoption of the latter strategy (named Strategy C), on the other hand, the online company can obtain a fixed proportion of its offline partner’s quasi rent. In the price competition, the online company chooses its optimal offline expansion strategy by predicting its profit in the post-expansion market.

This paper found that the equilibrium crucially depends on the synergy effect due to online–offline integration, and such synergy also influences both consumer and social welfare. This study shows the various conditions on the synergy that affect an online company moves toward offline markets. Accordingly, this finding can assist online companies with or without retailing business to choose an optimal strategy when expanding offline markets. Moreover, by doing some necessary welfare analysis, this study shows that the online company’s offline expansion is not always benefiting consumers nor be socially desirable, which may shed some lights on the possible competition policy in the case where online companies practice in offline expansion.

Different from conventional wisdom in online-offline integration, the theory indicates that the offline expectation of online company may not always benefit consumers nor be socially desirable. Moreover, the findings also shed some lights on the possible competition policy in the case where online companies practice in offline expansion.

The purpose of this study is to propose a new coordinated dynamic demand lot-size and delivery planning problem (CDLSDP), in which the delivery policy is integrated into the coordinated dynamic demand lot-size problem (CDLSP).

As a non-deterministic polynomial complete (NP-complete) problem, this CDLSDP seems difficult to be solved by a polynomial-time method. To handle this problem effectively and efficiently, a four-phase heuristic that balances the setup and inventory costs in the coordinating and delivery stages is designed to find near-optimal solutions.

Numerous computational experiments show that the proposed four-phase heuristic is effective and efficient. For 1,800 experiments with different scales, and different joint setup costs, solutions by the proposed heuristic have an average gap no more than 1.34% from the optimal solution.

To decrease total system cost, the CDLSDP optimizes the time-phased replenishment and delivery schedule, which includes joint setup cost, item setup, delivery and inventory cost, for each period. An effective and efficient four-phase heuristic is designed to solve the CDLSDP.

Compared with the traditional CDLSP, the delivery policy is considered by the new CDLSDP. Moreover, the proposed four-phase heuristic is a good candidate for solving the CDLSDP.

This case will enable students to understand the operations and business model of an international retailer. The case offers enough insights and learning on a retailer who enters a different market and collaborates with the local players to gain market access; and to understand the marketing techniques and strategies of an international retailer to capitalise on market opportunities.

The case is about a third largest US-based multinational Costco Wholesale corporation which is a giant retailer. The company operated at 803 locations with a revenue of $166.7bn, which makes it the third largest global retailer in 2020. The case offers comprehensive insight into Costco Wholesale’s business model, distribution strategy, marketing techniques and internationalisation. The authors further discuss that how Costco put forth its model among different range of customers and provided them with high-quality products at a comparatively lower price. The focus of the case is towards the Asian expansion of Costco. In subsequent parts, the strategies and challenges of Costco with respect to its Asian competitors have also been discussed. After generating experience in Asian markets, Costco has considered China as its next destination. The case also discusses the foreign retailers’ success, failure and retail format.

This case is designed for undergraduate and postgraduate classes of management and business administration.

Teaching notes are available for educators only.

CSS 8: Marketing.