Customer Demand Research Articles

Flexible material handling system for multi-load autonomous mobile robots in manufacturing environments: a hierarchical reinforcement learning approach

The increasing complexity of customer demands has led to the implementation of flexible job-shop scheduling and automated material handling systems across manufacturing sectors. In particular, advances in robotic technology have made autonomous mobile robots (AMRs) essential for material handling tasks within these sectors. The capability of free movement, path planning, and loading multiple work-in-processes (WIPs) can significantly enhance the efficiency of material handling operations. However, the full flexibility of AMRs cannot be utilised when their decisions regarding the sequence of loading and unloading multiple WIPs are made by specific rule-based operations, resulting in inefficiencies in the throughput of WIPs in manufacturing environments. To address this inefficiency, we introduce a hierarchical reinforcement learning algorithm to optimise material handling with AMRs, thereby maximising the throughput of WIPs. In this approach, a graph attention network (GAT) serves as an encoder for the hierarchical reinforcement learning (HRL) input, effectively capturing the complex relationships between different nodes. Computational experiments demonstrate that our approach enhances the efficiency of the material handling system more effectively than existing rule-based methods.

DUKPT for Software POS: A Technical Key Management Approach for Safeguarding Payment Data

Purpose: The paper explores how the Derived Unique Key per Transaction (DUKPT) encryption technique enhances the security of software-based Point of Sale (POS) systems, addressing rising cyber threats and safeguarding sensitive financial data. It aims to educate stakeholders across industries on DUKPT's implementation and long-term benefits in meeting evolving regulatory and customer demands for data security. Methodology: A thorough literature research and a hands-on examination of DUKPT's use in software-based point-of-sale systems comprise the methodology. Existing research on key management, encryption of payment systems, and the weaknesses of conventional key management techniques are all included in the literature review. The report also provides case studies that show how DUKPT has been implemented in various industries, looking at both technical details and practical results. The examination covers network communication protocols, device security measures, secure key storage, and PCI DSS (Payment Card Industry Data Security) compliance. The conclusions are further supported by quantitative data from security breach statistics and qualitative data from interviews with industry professionals. Findings: The findings of this paper reveal that DUKPT significantly enhances the security of software-based POS systems. Key results include: The Derived Unique Key per Transaction (DUKPT) encryption technique offers several advantages. It enhances security by generating a unique encryption key for every transaction, effectively reducing the risk of data breaches and preventing key reuse attacks. Additionally, DUKPT improves operational efficiency by allowing businesses to manage encryption keys securely without significant overhead, resulting in streamlined processes. Its implementation also demonstrates a stronger commitment to regulatory compliance, particularly with PCI DSS standards, minimizing the risk of penalties for non-compliance. Furthermore, the enhanced data security fosters greater customer trust, which ultimately strengthens client loyalty and retention Unique Contribution to Theory, Practice, and Policy: The study makes a unique contribution to the field by providing a thorough analysis of DUKPT's benefits, enhancing theoretical discussions on cryptographic techniques, educating policymakers about the need for updated security regulations to improve cybersecurity in payment systems, and providing useful case studies and suggestions for businesses looking to successfully integrate DUKPT in software POS environments.

Influence of Electronic Customer Relationship Management Strategy on Performance of Small and Medium Enterprises in Kenya

Despite the high cost of electronic customer relationship software solutions, its use can be justified as an investment in building long-term client relationships, improving customer retention, and, ultimately, boosting long-term profitability. As a result, it is critical for small- and medium-sized firms (SMEs) in Kenya to take a forward-thinking attitude and maintain their market survival by adapting to developing trends in customer relationship management. This is because the modern business setting has become exceedingly dynamic, necessitating small and medium enterprises to formulate strategies that align with the rapid evolution of technology, shifting customer demands, and intensified global competition to improve their performance. The findings indicate SMEs in Kenya are increasingly implementing relatively uncomplicated information and communication technologies to enhance their capabilities in customer communication and information management. This strategic move is aimed at gaining a competitive edge by leveraging electronic customer relationship management practices. Small- and medium-sized enterprises perceive the communication component of electronic customer relationship management as more manageable, yet encounter challenges in effectively incorporating client information into their decision-making processes. Overall, it can be observed that electronic customer relationship management implementation in SMEs is often characterized by an ad hoc approach rather than a strategic one. SMEs need to align electronic customer relationship initiatives with the overall strategic goals to enhance their overall performance.

Making the case for digital transformation: Digital entrepreneurship and on-demand service innovation

ABSTRACT Digital technologies have drastically changed customer demands, leading companies to re-evaluate their innovation strategies. Our empirical findings establish that digital entrepreneurship is critical in service innovation. The findings highlight that having a dedicated individual explicitly in charge of digital transformation significantly influences on-demand service innovation and, ultimately, a firm’s performance. By focusing on the impact of digital entrepreneurship on service innovation, this study provides a simplified model for digital transformation. It draws generalizable conclusions from the analysis of a sample of South Korean enterprises, informing future empirical studies on digital transformation and its effects on business growth.

Reconfigurable Manufacturing Systems: Enhancing Efficiency via Product Family Optimization

In response to the increasing complexity of modern production environments driven by heightened competition, customer demands, and sustainability goals, this work presents a focused methodology for forming product families within reconfigurable manufacturing systems (RMSs). Unlike traditional approaches, our method emphasizes the practical implementation of the Analytic Hierarchy Process (AHP) and the Average Linkage Clustering (ALC) algorithm to optimize RMS configurations. By evaluating specific comparison criteria—such as assembly sequence, machining sequence, components, production tools, and production demand—we aim to enhance resource utilization and adaptability to market changes. The proposed methodology enables a systematic assessment of RMS performance tailored to diverse product requirements. A detailed example of machining systems demonstrates the use of machining sequence and tool usage as primary criteria, showcasing the practical application and decision-making capabilities of the approach. This work contributes to the field by providing a structured framework for decision-making in RMS, facilitating efficient and precise product family formation to meet evolving manufacturing demands.

Factors affecting the adoption of RFID in the food supply chain: a systematic literature review

The unsustainability of the current food system raises food security concerns worldwide due to the population’s increased demand for fresh food and food safety. Unsafe food incidents lead to a high risk of poverty and economic loss. This includes food waste, safety, and security during the sustainable food system process from farm production to consumer. There is a need to implement a fast traceability system like Radio Frequency Identification (RFID) in the sustainable food system to ensure food quality and safety, meet customer demands, and achieve Sustainable Development Goals (SDGs): 1—No poverty, 2—Zero hunger and 13—Climate action for 2030 target. The study objective was to explore the factors that affect the adoption of Radio Frequency Identification (RFID) in the food supply chain. The study adopted the TOE (technology-organization-environment) framework to explore factors that affect RFID adoption in the food supply chain. The study utilized a systematic literature review to examine the TOE factors influencing the adoption of RFID in the food supply chain. The results indicate that technological (complexity, cost, and security), organizational (technical skill and management support), and environmental (maintenance and support, IT policies and regulations) are the major factors that affect the adoption of RFID in the sustainable food system industry. The study recommends organisations intending to adopt RFID allocate enough resources and be prepared to overcome RFID adoption external challenges. The study concludes that technological factors, organizational factors, and environmental factors are important factors for RFID adoption in the food supply chain. However, further empirical studies are necessary to overcome the challenges of systematic literature review based on secondary data and convenience sampling.

Effects and Determinants of Implementing Digital Customer Service Tools in Polish SMEs

The article aims to identify the effects and determinants of implementing digital customer service tools in Polish SMEs in terms of digital customer requirements. Quantitative research was conducted among Polish SMEs using a survey. The following statistical methods were used to analyze the survey data: Dunn’s post hoc tests, ANOVA Kruskal–Wallis test, Kendall’s rank correlation coefficient, and Multivariate Adaptive Regression Splines (MARSplines). Research results showed that Polish SMEs demonstrating better preparedness to serve digital customers achieve higher financial results, an increase in the rapidity and agility of customer service, increased customer satisfaction, and improved image. In addition, they gain sustainability benefits in the form of reduced emissions of hazardous substances or waste, recycling of waste, and reduced consumption of water, electricity, and other raw materials. The main determinants of digital transformation in customer service are the type of business (Polish Classification of Activities—PKD), the age of the company, and the educational level of its manager. The article contributes to promoting digitization among SME managers and motivates them to support customer service with digital tools. The identified effects and determinants provide practical guidance and encourage the implementation of digital technologies to meet the demands of digital customers. Using this approach, SMEs can increase their satisfaction and loyalty, resulting in better financial performance and improved competitiveness. This article identifies the economic and sustainability effects and determinants of implementing digital customer service tools in Polish SMEs in the context of digital customer requirements. This study has an original approach to the issue of digital transformation in the SME sector in Poland.

Multi-agent behavioral evolutionary game analysis of digital twin technology adoption in manufacturing enterprises

ABSTRACT Digital twin technology is crucial in breaking through the bottleneck of integrating the physical and information worlds in the manufacturing industry. However, manufacturing enterprises lack sufficient economic motivation and subjective willingness to adopt due to concerns about technological challenges and cost inputs. To elucidate the mechanisms that influence the adoption of digital twin technology, this study establishes an evolutionary game model from a stakeholder perspective, dynamically analyzes the strategy selection and system stability conditions of each participant and conducts numerical simulations. The findings reveal that the adoption process of digital twin technology in manufacturing enterprises occurs in phases. The coefficient of product attribute enhancement emerges as a key factor in promoting adoption. Government financial and consumption subsidies further encourage the adoption of digital twin technology and enhance customer preference for twin products and derivative services. The customer digital collaboration coefficient and demand matching coefficient significantly affect customers’ perceived utility benefits, which in turn influence manufacturing enterprises’ decisions to adopt digital twin technology by converting them into spillover benefits. Finally, this study provides targeted recommendations to various stakeholders to further promote the adoption of digital twin technology.

A novel machine-learning rolling horizon heuristic for dynamic lot-sizing and job shop scheduling problems

This study introduces an innovative approach to production planning and scheduling under uncertain customer demands by integrating uncertainty directly into the algorithmic framework. We present a novel rolling horizon simulation-based constructive heuristic to minimise total costs, encompassing production, setup, inventory, and backlog costs. We leverage priority rules to enable the method to adapt in real-time to changes. Our contributions include not only a novel heuristic but also the integration of a coevolutionary genetic programming-based hyper-heuristic, significantly improving solution quality and computational efficiency. Compared to other rule-based heuristics, our method consistently outperforms with an average reduction in total costs of 1.78%. Furthermore, it outperforms deterministic and two-stage stochastic programming models within a one-hour time limit, with reductions of 18.20% and 6.53%, respectively. Incorporating mathematical programming models into a rolling horizon scheme led to slightly lower total costs, with an average reduction of 0.13% and 1.16%. However, in less than half an hour, the proposed method reached better results in two out of three cases. The results of an efficiency and robustness analysis highlight the proposed method as a robust solution for dynamic and complex real-world applications.

The Efficiency of Temperature-Controlled Inventory Management: A Case Study of Convenience Store in Salaya Sub-District, Nakhon Pathom Province

Background and Aims: Current logistics management is an important goal that entrepreneurs can use as a source of competitive advantage. Both at the business level and national level. This is because of globalization that has resulted in more intense business competition. And greater trade liberalization As a result, the business sector must upgrade its ability to conduct business in every possible way. The purposes of this research were 1) to investigate the efficiency of temperature-controlled inventory management by studying personal factors, namely work experience, number of employees, position, and monthly average income. And study to investigate the factors of the inventory management system that affect the efficiency of temperature-controlled inventory management in convenience stores. Methodology: The questionnaire was used as a research instrument, it was collected from 15 samples. and collected the direct interviews with managers and employees who administer the inventory control. The statistics that were used were percentage, mean, and standard deviation. The statistics that were used to test the hypothesis were One-Way ANOVA. Results: The result of this study showed that among the sample of 15 convenience store staff, it was found that most of the staff had 1-5 years of work experience, with employees between 11-20 people in general positions, and an average personal monthly income of 10,001-20,000 baht. The hypothesis testing results revealed that the significance of the variables, work experience, position, and average monthly income was greater than the 0.05 level of significance. This indicated that despite differences in work experience, position, and average monthly income, there was no difference in the efficiency of temperature-controlled inventory management for the convenience store in Salaya, Nakhon Pathom. The results of the regression coefficient test revealed that there is only one independent variable had a significant impact on the efficiency of temperature-controlled inventory management of convenience stores. It was the replenishment system. The forecast coefficient was 40.8%. The remaining 59.2% is another factor apart from those mentioned above. For the replenishment system, according to the research results, entrepreneurs should pay great attention to product replenishment and always keep up with the needs of customers to be able to have enough customer service inventory. Conclusion: Work experience, position, and average monthly income do not affect the efficiency of temperature-controlled inventory management of convenience stores in the Salaya Subdistrict. The product replenishment system has an important effect on this efficiency at 40.8 percent. Product replenishment is a factor that entrepreneurs should give importance to to have sufficient inventory and meet customer demand in time.

Analisis Ketahanan Equipment Ballmill terhadap Pengaruh Oprasional Boiler dalam Penerapan Reability Centered Metode (RCM) Menggunakan Soft System Methodology

PT. Dian Swastatika Sentosa generates electricity through a private thermal power plant. This company produces steam and electricity for paper mills. The company hopes to meet its steam and electricity needs in 2023 with a boiler with a load capacity of 180 tons and a maximum capacity of 220 tons. However, from February to July 2023, that goal was not achieved. The most common problems faced by this company are the failure to conduct preventive inspections and timely machine maintenance, as well as the failure to carry out necessary repairs. Delays in machine repairs, which result in inconsistent machine downtime schedules to meet customer demand, leading to damage to boiler equipment, causing abnormal boiler operation and reduced steam production. This research aims to design equipment to withstand operational impacts using failure mode and effects analysis (FMEA) with the Soft Systems Methodology (SSM) and reliability-centered maintenance (RCM) techniques. The RCM method assists in identifying the processes that must be followed to guarantee that a machine or system performs as intended. RCM can also be used to design, choose, and create alternative maintenance methods that are focused on safety, operations, standards, and economics. For the entire problem in the investigation, a dynamic model is necessary. An analytical system is used in this model in order to recognize and duplicate the features of the overall system., as well as to provide repair solutions and address the burden of the problem. This research produces a presentation in the form of problem identification, causal loops, diagrams of machines that frequently experience failures, rich images of the causes and effects of the ball plate crusher liner damage, root cause definitions, and conceptual models for repair and maintenance. business productivity and debating process.

THE ROLE AND POSITION OF NUAULU WOMEN IN THEIR ANCIENT CULTUREON SERAM ISLAND, CENTRAL MALUKU

Nuaulu people men and women from in the past Already There is settings ( customs) customs ) that have been separate role and position Woman in public Nuaulu . Teachings ancestors like This show Woman Nuaulu No Can become leader in community , women No Can become a king, a woman No Can lead an event or tradition custom Nuaulu , female No Can become head soa , woman No Can become Saniri chief , female No Can guard House customs and so on . All form prohibitions to Woman Nuaulu This in a way clear to show difference between role and position women and men Nuaulu . Reality life Woman Nuaulu in Nua Nea Country is located in one transition awareness that role they limited / weak / low from men , even though method think they the more complex with current developments .​ Study This discuss about roles and positions Woman ethnic group Nuaulu in culture ancestors which has been maintained from generation to generation until now. Study This uses a qualitative method with a descriptive approach. Data collection through in-depth interviews with informants and observations looking at the roles and positions Woman Nuaulu in traditional ceremony / ritual process Nuaulu tribe. The results of the study showed that The role and position of Nuaulu women in Nuaulu traditions and traditional rituals cannot be separated from ancestral beliefs which have become guidelines and teachings from generation to generation for the Nuaulu people. that is birth ceremonies, hair-shaving ceremonies ( Tihti Kuau ), girls' coming-of-age ceremonies ( pinamou ), boys' coming-of-age ceremonies ( pahateri ), marriage ceremonies, and death ceremonies (autotu nimoe). which shows role and position Woman Nuaulu in a way customs are regulated based on customary ritual processions , namely demands women 's customs given authority For implement it and demand custom in the form of prohibition custom or taboo for Woman For follow as well as in its activities . While for teenage/adult women who are not yet married or still in school, their roles and positions they are more interested in the development of modernization, concentrate on their education , TV information, android phones (face book, WA, Youtube), and they still obey the norms and values of customs that have been taught by parents, and traditional figures. While for women who are already married, they still carry out all customary provisions with all the processions of traditional ceremonies from birth to death (life cycle) and they are afraid of violating customary rules because of the sanctions (ancestral sanctions). They do not want to go against customary provisions because it has a disastrous or unfortunate impact on women, families and society.

A Machine Learning Method to improve Supplier Delivery Appointments in Supply Chain Industries

Goal: The paper aims at the customization of supplier schedules upon the priority of key articles. It aims at the prediction of an appointment to a supplier based on the key aspects. The objective of this study is to investigate whether the machine learning algorithms can be used to predict the delivery dates of the products based on the trained data. Design/Methodology/Approach: The prediction method uses a machine learning approach. Prediction algorithms namely, Logistic Regression (LR), K-Nearest Neighbour (KNN), and Random Forest (RF) are used for forecasting. The appointment is assigned to a supplier based on the delivery date of a previous supplier order. If a supplier requests a prior date, then the average sales and opening stock of the products is verified and the prior date of n-3 will be assigned (‘n’ represents the assigned days of delivery). Results: Clustering is used to visualize the group of products based on the days of delivery and quantity ordered. This helps in creating the floor space for the on-time delivery of fast-moving products and reducing the manual process for the reordering team. The present work can be used for the procurement of key articles for the fulfillment of customer demands. The combination of K-Means with prediction and classification is giving lesser expected delivery date using RF compared to LR and KNN method. Limitations: The limitation of the current work is that it is applicable for small scale industries in the developing countries. Also deployment of the application in agricultural sectors allow for greater transparency and accountability in the supply chain. Practical Implications: Further, the work will also provide recommendations for retail companies looking to implement machine learning algorithms in their supply chain management. Originality/ Value: The case study developed a model for Retail industries to manage the supplier delivery appointments.

Fee or free? Re-think the role of service fees in omnichannel retailing after the pandemic

Many UK high-street retailers leverage their brick-and-mortar stores to implement omnichannel strategies. This strategy drives online traffic into stores by allowing online customers to collect in-store. Due to the COVID-19 pandemic, retailers have endured soaring operational costs and plummeting store footfall, and customers have become more price-sensitive when the cost-of-living crisis bites. This situation leads to a trade-off: charging a collection fee may deter customers from purchasing, whilst offering free collections could cause a financial loss. This paper develops a stylised model to understand how omnichannel collections affect customer demand and retailer profitability after the pandemic. We consider three omnichannel collection scenarios based on observed practices: free, discounted, and fixed rate. Our results show that a collection fee can positively steer customer demand across channels and improve retailer profitability, and the optimal omnichannel policy exists. The collection fee should also be jointly determined with the existing home delivery fee.

Operational strategy, capabilities, and successfully accomplishing business strategy

This study investigates the vital role of corporations’ operational capabilities, which involve resources, competencies, and processes, in attaining the business’s strategic goals for profitability and sustainability. The methodology employs a selective literature review to analyze case studies, books, and articles that give an overview of operational management and its importance in achieving corporate goals. The results exhibit the challenges posed by rapid market changes, revealing the deficiencies of traditional operational systems focused solely on efficiency and cost. To attain sustained success, manufacturers must focus on a client-valued approach, align objectives with capabilities, and support inter-functional links. Companies with distinctive managerial processes outperform in profitability, emphasizing the significance of investing in management capabilities. Operational excellence necessitates a focus on efficiency, innovation, and customer experience, prompting a shift towards a learning style that encourages innovation. Aligning innovation efforts with business strategy is essential for sustainable competitive advantage. Technological innovation, particularly AI adoption, plays a transformative role in operational innovation, highlighting the importance of dynamic capabilities in managing technological change. Yet, effective inventory and supply chain management are important for meeting customer demand and maximizing efficiency through collaboration and adaptable control.

A note on valid inequalities for a service center location problem with a type of decision-dependent customer demand

A note on valid inequalities for a service center location problem with a type of decision-dependent customer demand

Hierarchical Membrane Computing Algorithms for Optimizing Customer-to-Green-Manufacturer Decision-Making in Industrial Internet Platforms

This paper proposes a dynamic membrane algorithm (DMA)-oriented computing framework designed to optimize decision-making in Customer-to-Green-Manufacturer (C2GM) operations on industrial internet platforms. Unlike traditional methods that focus solely on economic metrics, the DMA integrates membrane computing principles with evolutionary optimization techniques and incorporates green manufacturing objectives (e.g., energy efficiency, waste reduction, carbon footprint). By doing so, it dynamically aligns customer demands with manufacturing capabilities in real time, ensuring both operational efficiency and environmental stewardship. The DMA facilitates parallel and hierarchical processing of complex decision tasks, mapping evolutionary rules and manufacturing operations into a structured membrane system that accelerates convergence and improves scalability. Experimental evaluations—both in controlled simulations and a real-world case study of C2GM operations in Yiwu—demonstrate that the DMA not only achieves faster and more stable convergence than genetic algorithms but also supports greener production processes. This integrated approach thus enhances strategic decision-making, offering a sustainable pathway for advancing industrial internet ecosystems and global supply chains.

Exploring Sensory Attributes in Spinach- and Offals-Filled Chicken Roulades: An Empirical Analysis.

One of the most significant industries in the world is the meat sector, and development into new goods is ongoing due to high customer demand and fierce market competition. Products made from chicken are widely favored. This phenomenon can be attributed to the lack of cultural or religious restrictions on this meat. The study looks into how using two distinct types of iron-rich fillings impacts the sensory profile of classic chicken roulades. The purpose of the study is to determine how changes in sensory qualities (such as taste, texture, and flavor) affect product acceptance among customers. This approach uses methods like check-all-that-apply (CATA), principal component analysis (PCA), external preference mapping (PrefMap), and penalty analysis to explore the impact of adding chicken offals and spinach as fillings on the sensory profile of traditional chicken meat roulades. This approach seeks to expand the meat product category, create new goods that use both plant and animal components, invent new ways to use offals and spinach in the market, and ensure that consumers accept these new products. Based on the results of our investigation, the type of filling utilized in the roulades showed the most differences across all sensory tests. According to hedonic analysis and preference mapping (PrefMap), the majority of customers favored roulades with spinach fillings as opposed to those containing chicken offals, which only a small portion of customers liked. Variations in consumer preference for roulades filled with chicken offals were noted in the anatomical region, with slightly greater preference for roulades made from chicken breast. However, this (anatomical region used) did not significantly affect the outcomes of all sensory tests. The spinach stuffing was found to be quite popular with the customers, even outperforming traditional chicken roulades, making it the most significant influence. Based on consumer appreciation, this suggests that the spinach-filled chicken roulades may be a viable option for meat products in the future.

Nanogrids in Modern Power Systems: A Comprehensive Review

Nanogrids are becoming an essential part of modern home power systems, offering sustainable solutions for residential areas. These medium-to-low voltage, small-scale grids, operating at medium-to-low voltage, enable the integration of distributed energy resources such as wind turbines, solar photovoltaics, and battery energy storage systems. However, ensuring power quality, stability, and effective energy management remains a challenge due to the variability of renewable energy sources and evolving customer demands, including the increasing charging load of electric vehicles. This paper reviews the current research on nanogrid architecture, functionality in low-voltage distribution systems, energy management, and control systems. It also explores power-sharing strategies among nanogrids within a microgrid framework, focusing on their potential for supplying off-grid areas. Additionally, the application of blockchain technology in providing secure and decentralized energy trading transactions is explored. Potential challenges in future developments of nanogrids are also discussed.

Online Learning and Pricing for Multiple Products With Reference Price Effects

ABSTRACTWe consider the dynamic pricing problem of a monopolist seller who sells a set of mutually substitutable products over a finite time horizon. Customer demand is sensitive to the price of each individual product and the reference price which is formed from a comparison among the prices of all products. To maximize the total expected profit, the seller needs to determine the selling price of each product and also select a reference product (to be displayed) that affects the consumer's reference price. However, the seller initially knows neither the demand function nor the optimal reference product, but can learn them from past observations on the fly. As such, the seller faces the classical trade‐off between exploration (learning the demand function and reference price) and exploitation (using what has been learned thus far to maximize revenue). We propose a rate‐optimal dynamic learning‐and‐pricing algorithm that integrates iterative least squares estimation and bandit control techniques in a seamless fashion. We show that the cumulative regret, that is, the expected revenue loss caused by not using the optimal policy over periods, is upper bounded by where hides any logarithmic factors. We also establish the regret lower bound (for any learning policies) to be . We then generalize our analysis to a more general demand model. Our algorithm performs consistently well numerically, outperforming an exploration‐exploitation benchmark. The use of price experimentation and estimation techniques could be readily applied in real retail management.