Retail Value Research Articles

The contribution of organic private label products to private label share outcomes

PurposeThe growing demand for sustainable consumption motivates retailers to consider including organic private label products in private label assortments to attract and serve health and environmentally conscious consumers, while also possibly improving the image of the private label brand as well. This study aims to examine the impact of prioritizing organic private label products in private label assortments on private label share outcomes.Design/methodology/approachTheoretical predictions are empirically examined using a comprehensive store panel sales data set covering 50 distinct metropolitan markets in the USA from 2008 to 2011 in the yogurt product category.FindingsFindings indicate that private label products may provide strategic value for certain retailers, based on a variety of private label assortment, national brand competition and retailer characteristic dimensions.Research limitations/implicationsThis research serves as initial empirical evidence on how organic products may influence private label category share. Future research should consider additional product categories and geographic markets and also seek to understand consumer perceptual factors in more detail.Practical implicationsRetail managers can better understand the role that organic products play in private label portfolios.Originality/valueWhile much previous work has examined how organic products sell relative to conventional products and a sizable literature has investigated private label brand strategy, little research has explicitly examined the role of organic products within private label assortments.

Assessing Ecological Compensation Policy Effectiveness: A Case Study in the Inner Mongolia Autonomous Region, China

As a vital component of the terrestrial ecosystem, grassland accounts for one-third of the global vegetation system. Grassland degradation has been exacerbated due to extreme overgrazing in China’s Inner Mongolia Autonomous Region (IMAR). While conservation was carried out via the Ecological Subsidy and Award Program (ESAP) to mitigate grassland degradation, little is known about its effectiveness in improving the biophysical conditions of grassland. This paper integrates the conceptual frameworks of total socio-environmental systems (TSESs) to assess how ecological systems respond to the ESAP, investigate the spatial heterogeneity of the ESAP, and explore the meddling effects of socio-environmental interactions on the ESAP. We integrated ecological, climate, and socioeconomic data and developed several hierarchical linear mixed models (HLMMs) to investigate how these factors interact with the ESAP in the IMAR. Our findings prove that the above-ground biomass between 2011 and 2015 responds significantly to variations in socioeconomic conditions and ecological communities. Available land resources, hospital and medical facilities, and net farmer and herdsman income are the most critical factors positively related to grassland productivity. Primary industries like mining, total consumer retail value, farming, forestry, animal husbandry, fishery productions, and GDP are the most damaging factors affecting biomass. Our study recommends a regionally or locally tailored ecological recovery policy, instead of a generalized one, in future efforts to conserve grassland.

A Comprehensive Review of Carbon Capture, Utilization, and Storage (CCUS): Technological Advances, Environmental Impact, and Economic Feasibility

Carbon capture, utilisation, and storage (CCUS) technologies are critical to reducing CO2 exhalations on a global scale. This review study synthesizes the many elements of CCUS over 50 years, from R&D to deployment scales, in terms of their mitigation potential for global emission reductions. Next, it discusses existing and new carbon capture techniques from an automation standpoint (e.g., pre-combustion capture, post-combustion capture combustion), as well as the economic feasibility of CCUS regionally in terms of capital retail price, operating expenses, and value in the form of potential revenue streams based on CO2, aided by significant range-scaling building blocks such as rising nation. Each technique is thoroughly evaluated in terms of its environmental impact and associated risks, and case studies are used to illustrate practical lessons learnt. The paper also discusses the arguments around what future advances may exist in CCUS technology, and opportunities to scale these up (including research needs for this support), drawing lessons past policy. The findings underscore the importance of integrating CCUS into broader climate strategies to achieve net-zero exhalations while addressing the economic and environmental challenges that remain.

The “6th R” of sustainability: Repurposing operating room waste for community benefit

BackgroundOperating rooms contribute greatly to hospital waste and greenhouse gas production. Efforts to “green the operating room” have focused on the 5R's of sustainability: reduce, reuse, recycle, rethink, and research. We propose a “6th R” —repurposing— as simple yet effective means of addressing operating room waste. MethodsClean, non-reusable surgical supplies were collected from a satellite facility of a children's hospital during a six-week pilot program. Materials were catalogued and repurposed throughout the community. The potential financial benefits were estimated based upon the value of repurposed goods and savings from reduced waste disposal. ResultsOver 960 items were collected during the 6-week pilot. Materials ranging from plastic trays to surgical towels were donated to organizations throughout the community. Approximate retail value of repurposed items was over $1200. When extrapolated to the entire hospital system, these repurposing efforts could account for over $50,000 in donations and $1300 in operational savings over a calendar year. ConclusionsRepurposing unused surgical items provide environmental, societal, and financial benefits, all while promoting more sustainable healthcare systems.

How does omnichannel retailing deliver customer value? Insights from science mapping and future agenda

ABSTRACT Retailers need to adopt an omnichannel strategy to survive and thrive in the digital era, considering the industry’s competitiveness and technological disruption. If sources of consumer value in omnichannel commerce are not fully understood, retailers may not be able to respond and adapt to this crucial transition since customers are value-conscious in addition to having changing buying habits. Our study aims to uncover sources of customer value specific to the context of omnichannel retailing. Bibliometric data from 295 Scopus-indexed articles related to customer value in omnichannel retailing was retrieved and subjected to network analysis and science mapping using VOS Viewer and Biblioshiny app respectively. Our findings identified five clusters of customer value in omnichannel retailing and seventeen research themes that can be classified into four categories (established, emerging, niche, and basic). Based on these insights, we propose five dimensions of omnichannel retail value. Additionally, a future research agenda for the field is offered along with the identification of core research gaps.

Vehicle-to-Grid Revenue from Retail Time-of-Day Rates, Compared with Wholesale Market Participation under FERC Order 2222

This article compares potential revenue from electric storage in retail and wholesale electric markets. The retail value can be extracted when storage responds to time-of-day retail prices. The wholesale value is enabled by the recent US Federal Energy Regulatory Commission Order 2222, which requires regional transmission operators (RTOs) to allow distributed storage behind the meter to participate in wholesale electric markets. To quantify the value of these markets, we use realistic time-of-day rates and market prices in one RTO’s ancillary service market. Formulae are developed to estimate the value of behind-the-meter storage in wholesale and retail markets, using an example electric vehicle in a fleet setting. The formulae are also used to compare whether or not net metering is available and different charging rates. The aggregate national storage behind the retail meter is very large, given the projected growth of electric vehicles. Our findings indicate the revenue from wholesale markets can be significantly more than that of retail opportunities. However, the potential in either retail or wholesale markets is currently limited by both state policy and incomplete RTO implementation of FERC orders.

Collusion and Price Behavior in the U.S. Pork Industry

Abstract This research analyzes the U.S. pork industry dynamics in light of the alleged output price-fixing cartel of the largest pork processors revealed in the antitrust lawsuits filed by pork buyers beginning in 2018. The empirical evidence may suggest that pork production, the farm, wholesale, and retail values of pork, and marketing margins increased, but the farm sector share decreased in the cartel period (2009–2019), as compared with the pre-cartel period (1998–2008). The wholesale pork pricing by pork processors is consistent with oligopoly pricing in both the pre-cartel and cartel periods. While the estimated decrease in cost pass-through between these two periods may reflect an increase in the seller (oligopoly) market power of pork processors in the cartel period, this cost pass-through decrease is not statistically significant from zero. The retail pork pricing by food retailers is consistent with perfectly competitive pricing in both the pre-cartel and cartel periods.

Tricks of the trade: Understanding and utilizing influencer tactics to improve retailer performance

Despite their impact on contemporary purchase decisions, academic research has given little attention to how social media influencers are impacting the retail ecosystem. This paper sets out to change this by contributing a better understanding of the impact of influencers on retailing activities. Using an explanatory sequential mixed method, we first conduct a survey of consumers’ use of influencers in their purchase decisions. Specifically, we map and compare consumer perceptions of how influencers and retailers perform on different retailing activities. To better understand the differences found, we then conduct focus groups that explore how consumers use and derive value from influencers in their purchase decisions. Our findings highlight how influencers create retail value, and that, in many cases, they are doing so better than retailers themselves. We summarize our findings in terms of learnings for retailers and discuss how influencers may even challenge our notion of retail. We provide strategies that retailers can employ to both work with and mitigate the effect of influencers and call for more research on influencers from a retail perspective.

Exploring the investment value of retail sales growth: Evidence from the China Retailer Alliance

This study investigates the investment value of retail sales growth using a unique dataset obtained from the China Ants Alliance, a retailer alliance in China. Leveraging this dataset, we construct a weekly retail sales growth rate index (SG) and draw significant conclusions about consumer-oriented firms. The hedge portfolios constructed based on this index earn a 0.206% excess weekly return. The predictability of the returns from the index persists after controlling for various firm characteristics. Sales growth also positively predicts firms’ fundamentals, such as revenue growth and cash flow surprises, highlighting the investment value of retail sales in predicting future cash flows and a firm’s revenue. Overall, we enrich the literature on consumer behavior information and stock pricing. We further expand the exploration of the investment value of nonfinancial information and provide a valuable reference for investors and the capital market.

AI-DRIVEN PREDICTIVE ANALYTICS IN RETAIL: A REVIEW OF EMERGING TRENDS AND CUSTOMER ENGAGEMENT STRATEGIES

As the retail landscape undergoes a profound transformation in the era of digitalization, the integration of Artificial Intelligence (AI) and predictive analytics has emerged as a pivotal force reshaping the industry. This paper provides a comprehensive review of the latest trends in AI-driven predictive analytics within the retail sector and explores innovative customer engagement strategies that leverage these advanced technologies. The review begins by elucidating the foundational concepts of AI and predictive analytics, highlighting their synergistic role in forecasting consumer behavior, demand patterns, and market trends. The paper then delves into the emerging trends, such as machine learning algorithms, natural language processing, and computer vision, that are revolutionizing the way retailers harness data for strategic decision-making. In addition to outlining technological advancements, the paper emphasizes the crucial role of data quality and ethical considerations in the implementation of AI-driven predictive analytics. It examines the challenges associated with privacy concerns, algorithmic bias, and the need for transparent AI models to ensure responsible and fair use of customer data. Furthermore, the paper explores a spectrum of customer engagement strategies enabled by AI-driven predictive analytics. From personalized shopping experiences and targeted marketing campaigns to dynamic pricing and inventory optimization, retailers are deploying innovative approaches to enhance customer satisfaction and loyalty. The review also discusses case studies of successful AI implementations in leading retail enterprises, showcasing tangible benefits such as improved operational efficiency, increased sales, and enhanced customer retention. These real-world examples illustrate the transformative impact of AI-driven predictive analytics on diverse aspects of the retail value chain. By examining emerging trends and customer engagement strategies, it serves as a valuable resource for industry professionals, researchers, and policymakers seeking to navigate the evolving landscape of AI in the retail sector.
 Keywords: AI-driven Predictive Analytics, Retail Industry, Customer Engagement Strategies, Machine Learning Algorithms, Natural Language Processing.

Tobacco market trends in 97 countries between 2007 and 2021.

Analysis of the tobacco market can provide valuable insights for developing tobacco control strategies. This study examines the market trends of cigarettes, cigars/cigarillos, smoking tobacco, smokeless tobacco, e-cigarettes, heated tobacco products (HTPs), and tobacco-free oral nicotine, across 97 countries between 2007 and 2021. We obtained annual tobacco retail value data from Euromonitor Passport and calculated the market share for each type of tobacco product. The research examined trends in retail value and market share globally, stratified by national income level, as well as in individual countries. From 2007 to 2015, the growth of the global tobacco market was primarily driven by cigarette sales. However, starting in 2016, emerging products, including e-cigarettes, HTPs, and tobacco-free oral nicotine, as well as non-cigarette combustible products, including cigars/cigarillos and smoking tobacco, have been mostly responsible for the increases in the global tobacco retail value. High-income countries experienced the greatest increase in the retail value of emerging products, while middle- and low-income countries still observed rises in cigarette sales. Trends in the retail value of different tobacco products varied widely during the study period, with distinct trends observed in different income levels and within individual countries. These trends can supplement prevalence data and be used to inform local tobacco control policies.

IoT Based Design and Implementation of Intelligent Energy Distribution Management with Photovoltaic System

Abstract: The grid operators have difficulties as a result of the increasing penetration of renewable sources due to reduced environmental contamination. Unrestrained energy use will undoubtedly deepen environmental harm and accelerate global warming. A best practice for effectively managing energy use is energy management. IoT technology can be leveraged by technological advancements to facilitate energy management. This paper offers a novel way to energy management using a solar system and the Internet of Things (IoT). The suggested system tracks, evaluates, and optimizes solar power use in real time with the goal of increasing energy distribution's intelligence and efficiency. The project's goal is to build a net energy meter (NEM), a unique billing system that gives solar PV system owners credit for the entire retail value of the electricity their system produces. Under NEM, a customer's electric meter tracks how much energy they use as well as how much extra energy the system produces and feeds back into the electric utility grid.

“With great power comes great responsibility”: Exploring the role of Corporate Digital Responsibility (CDR) for Artificial Intelligence Responsibility in Retail Service Automation (AIRRSA)

Scholars conceptualized the role of Corporate Digital Responsibility (CDR) to emphasize the ethical issues unique to the digital context by pushing all the actors involved in developing and integrating digital technologies and related data processing to act ethically and responsibly. However, how to apply AI services more ethically and develop AI equipped with moral/ethical intelligence are still open questions.Accordingly, this paper aims to understand the managerial applications and tools of Corporate Digital Responsibility (CDR) in AI retail service automation to identify the CDR value for consumers and retail managers. We link the five AI intelligence types (verbal-linguistic, logic-mathematical, visual-spatial, social, and speed-processing) to CDR strategies to produce value for retailers and consumers. Specifically, we define intelligent retail service automation, emphasizing actions, tools, and (privacy) concerns, and discuss the role of CDR in AI for intelligent retail service by developing the new concept of Artificial Intelligence Responsibility in Retail Service Automation (AIRRSA). Finally, we provide implications for scholars, managers, and policy-makers while proposing future challenges.

Immunomodulators as objects of the pharmaceutical market. Message III. The product conjuncture of immunosuppressants and their place in the state guarantees program of medical care of the population

Immunosuppressants (ІS) are used to prevent a number of autoimmune diseases, non-autoimmune inflammatory diseases and rejection of transplanted organs. Global ІS market is characterized by high growth rates.
 The aim of the work: analyze the immunosuppressants product nomenclature on the pharmaceutical market of Ukraine, as well as their characteristics from the point of view of state guarantees of medical care of the population.
 The research materials: the sources of special and scientific and methodical literature; The State Register of Drugs of Ukraine (as of February 1, 2023), the Register of Drugs that are subjects to reimbursement by the state guarantees program of medical care of the population, as of February 14, 2023. The methods of information search, analysis, generalization, and marketing research have been used.
 It has been established that 27 INN of immunosuppressants in the form of 134 trade names had been registered in Ukraine. Almost half of the studied drugs consisted of lenalidomide (23.13%), tacrolimus (15.67%) and mycophenolic acid (9.70%). Immunosuppressants are presented in the shape of 7 dosage forms, mostly in capsules (55.22%).
 It has been found that immunosuppressants are characterized by absolute import dependence, 127 foreign manufacturers from 27 countries have registered 133 trade names (99.25%), and the Ukrainian manufacturer (JSC "Farmak") - only one position (0.75%) and even that is from products in bulk. Germany is characterized as the country that has the highest production activity of immunosuppressants (22.83% of the enterprises had an indicator of production activity of 20.81%), and among the producers there are two pharmaceutical enterprises: Novartis Pharma Stein AG, Switzerland and Sinton Hispania S.L, Spain (production activity indicator 3.76% both).
 The Register of drugs subjects to reimbursement under the state guarantees program of medical care of the population has included 5 INN of immunosuppressants in the form of 21 trade names for people in the post-transplantation period. Four-fifths (80.95%) of them belong to expensive drugs, as evidenced by their retail price per package of UAH 1,000 or more. However, patients can receive 15 trade names free of charge, for the other 6 trade names patient’s payment ranges from 8.09 to 33.95% of retail value.
 The obtained results can serve as a prototype for the formation of the product nomenclature of drug manufacturers, wholesale pharmaceutical enterprises and pharmacies.

Agricultural Tractor Retail and Wholesale Residual Value Forecasting Model in Western Europe

The residual value of agricultural tractors plays a pivotal role in the financial viability of agribusiness enterprises. Nevertheless, there is a dearth of comprehensive studies concerning the prognostication of both retail and wholesale residual values specific to agricultural tractors within the context of Western Europe. This research introduces an innovative methodology for assessing the residual worth of agricultural tractors, with particular consideration given to the substantial pricing discrepancies between retail and wholesale transactions. Leveraging publicly available auction data, we develop a polynomial regression model aimed at forecasting the intricate relationship between retail and wholesale residual values. Notably, the model demonstrates an exceptional robustness, surpassing previous research endeavors, as evidenced by a remarkably low root-mean-square error (RMSE) of 0.0159 and a combined adjusted coefficient of determination (RSqAdj) of 0.9997. The findings of this study offer invaluable insights into a diverse array of stakeholders, empowering them to make well-informed decisions regarding machinery specifications, investment strategies, and asset disposal choices, thereby facilitating optimal financial performance.

Using Artificial Intelligence for Retail Value Chain

The present study aims to prove hypotheses regarding artificial intelligence integration in retail value chains in the post-Soviet economic space. Hypotheses were proven within a comprehensive research project based on the use of quantitative research methods (questionnaires), which allowed studying the opinions of 512 retail managers in Azerbaijan, Kazakhstan, and Tajikistan. A specially designed questionnaire eliminated ambiguity in results interpretation by including both simple closed questions with a single choice and questions using a Likert scale. All the formulated hypotheses were proven, leading to the conclusion that the retail market of the post-Soviet economic space is not ready for the introduction of robotization and full automation of retail stores. The study results can be used by retail managers in the post-Soviet economic space as they choose the direction of artificial intelligence integration.

Profiling ultra-processed foods in Thailand: sales trend, consumer expenditure and nutritional quality

BackgroundUltra-processed foods (UPF) are associated with adverse health outcomes. This study aimed to analyse the national trends in retail sales, consumer expenditure and nutritional quality of UPFs in Thailand.MethodsThe study used data from the Euromonitor Passport database for analysis of retail sales and consumer expenditure, and from the Mintel Global New Products Database for nutritional analysis using the WHO Southeast Asian Region nutrient profile model.ResultsThe study found the highest per capita sales volume and value of UPFs in 2021 were sauces, dressings & condiments (8.4 kg/capita) and carbonated soft drinks (27.1 L/capita), respectively. However, functional & flavoured water, ready-made meals and baked goods had the highest observed (2012–2021) and expected (2021–2026) sales growth. Supermarkets were responsible for most of the UPF sales since 2012, but convenience stores had larger growth in retail values. Growth in consumer expenditure per capita on UPFs from 2012 to 2020, ranged between 12.7% and 34%, and till 2026 is forecast to grow between 26% and 30%. More than half of UPFs exceeded at least one nutrient cutoff, 59.3% for total fats, 24.8% for saturated fats, 68.2% for total sugars and 94.3% for sodium.ConclusionsThe findings suggest a need for regulatory and non-regulatory measures such as UPF taxation and marketing restrictions, and market incentives for producing non-UPFs. A system for regularly monitoring and evaluating healthiness (both nutritional and processing aspects) of food products, especially UPFs, is required.

Exploring digital transformation and technological innovation in emerging markets

PurposeThis research aims to fill the research gaps regarding customer preferences for digitalisation to create value for retailers and customers, as well as focus on retail change and shopping behaviour in grocery retail stores in the emerging market.Design/methodology/approachThis paper contributes to the research in this area by evaluating customers' and retailers' attitudes towards digital transformation in retailing through interviews. Methodologically, 200 questionnaires were gathered, and data were analysed with the partial least squared structural equation modelling method.FindingsThe findings of this study reveal that the effect of digital transformation in the retail industry will be more apparent in an emerging market.Originality/valueThe paper's originality consists in understanding the future retail structure in an emerging market. Notably, focussing on business-to-consumer businesses appears helpful in distinguishing between behavioural (buying) intention and online buying behaviour (actual usage) in an emerging market.

Predator damaged eel caught in coastal fisheries of the Baltic Sea

Fish stock assessment may be constrained by incomplete knowledge on all mortality sources. Seal and cormorant raiding fishing gear to access the catch has been asserted by fishers to be a considerable problem in the small-scale European eel fishery along the Swedish Baltic Sea coast. We analysed logbook data and found predator losses in fisheries at 13.6 ± 12.6% among catches landed in 16 Swedish harbours in subdivisions 25, 27 and 29 of the Baltic Sea in 2019–2021. These numbers were used to assess the total predator damage along this coast at 12 ± 10 tonnes of caught eel at a landings value (about 10% of the retail value) of 105,000 ± 97,000 euros in 2020. This may constrain prospects of the declining commercial small-scale coastal eel fishery. Moreover, this quantitative estimate may be useful in future assessments of the local stock component, with potentially important implications for ecological, economic and social sustainability.

What Makes People Feel Empathy for AI Chatbots? Assessing the Role of Competence and Warmth

With the growth of contactless shopping, artificial intelligence (AI) chatbot services have become an effective tool for brands to interact with consumers. We investigate the effects of AI chatbots’ humanlike characteristics on consumers’ acceptance of chatbot services by mediating competence, warmth, and empathy based on the AI device use acceptance (AIDUA) model. Using structural equation modeling, we tested how the relationship between these variables differs depending on one’s need for human interaction. Findings suggest that AI chatbots’ personalization and anthropomorphism significantly increase perceived competence and warmth, leading to empathy. This positively affects consumers’ willingness to use AI chatbots. Consumers’ need for interaction moderates the relationship between anthropomorphism and competence. We applied a valid theoretical model to explore how the humanlike characteristics of AI chatbots affect consumers’ cognitive and emotional reactions, determining their service acceptance. The findings have practical value for online retailers who use AI chatbots as marketing communication tools.