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This paper presents a local energy exchange mechanism to benefit residential customers and retailers under variable wholesale market spot prices. To do so, a peer-to-peer (P2P) trading-enabled local energy market (LEM) is proposed to facilitate frequent energy transactions among participants. The proposed LEM mechanism considers market operational constraints and maximises electricity cost reductions. Further, the proposed LEM optimises the customers' investment return for battery energy storage systems (BESSs) and minimises retailers' financial losses during higher spot prices in the wholesale market. Finally, a case study is demonstrated using real-world Australian data in which P2P trading is performed between interested buyers and sellers. Two scenarios with high and low wholesale market spot prices are analysed comprehensively considering five metrics such as solar-to-spot (STS); solar-to-load (STL); forward buy contract (FBC)-to-load (FBC-L); spot-to-load (Short); and FBC-to-spot (Long). The simulation results reveal that the customers reap substantial benefits from the proposed LEM in contrast with business-as-usual (BAU), allowing them to expedite BESS investment returns. Also, the proposed LEM helps a retailer decrease the effect of higher spot prices by reducing its unexpected financial losses while improving self-consumption and self-sufficiency in the local energy network. • Proposing a spot price-aware local energy exchange framework. • Incorporating a retailer and a network operator into the proposed model. • Examining the impact on retailer's energy exchange during unstable spot prices. • Assessing the financial benefits offered to customers and stakeholders. • Evaluating how battery investment returns of customers are impacted. [ABSTRACT FROM AUTHOR]

• Retailers expressed frustration over loss of sales to neighboring states due to the Act. • There is a need for increased education around the Act for all stakeholders. • Findings support benefits of adjacent states enacting flavored tobacco sales restrictions. In November 2019, the Massachusetts legislature passed An Act Modernizing Tobacco Control and became the first state to restrict retail sales of all flavored (including menthol) cigarettes, e-cigarettes, and other tobacco products. Our study aims to provide the retailer experience of the new law from the perspectives of multiple stakeholders, including tobacco retailers themselves, public health officials, and Massachusetts residents. We conducted in-depth interviews with seven tobacco retailers and ten public health officials from March 2021 to April 2022. Monthly repeated cross-sectional surveys were administered through the online survey panel Prodege from April 2021 to August 2022 (adult sample: N = 765; adolescent sample: N = 900). Themes from interviews were identified by drawing on deductive codes informed by the interview guide, followed by inductive coding of data. Survey data were descriptively analyzed in R. Key themes included retailer frustration over loss of sales to neighboring states, factors associated with retailer compliance, and the need for increased education regarding the law. Survey results showed that a minority of adolescents (13.3%) and adults (26.1%) who vaped in the past 30-days were traveling to border states to purchase vape products. Less than one-quarter of adolescent participants and less than half of adult participants could correctly identify which products Massachusetts did not sell. Evidence from the retailer, public health, and end-user perspectives support mutual benefits of adjacent states enacting flavored tobacco sales restrictions, improved policy education for retailers and the public, and improved retailer enforcement. [ABSTRACT FROM AUTHOR]

Electric vehicle (EV) load integration and environmental concerns in recent years have motivated energy users to step forward in reducing carbon footprints by promoting energy trading. In the energy trading market, different energy stakeholders participate in trading energy with each other to maximize their utilities and improve trading efficiency. The social welfare (SW) of the energy market plays a significant role in keeping the market going and motivating new users to engage in energy trading. The SW of the energy market depends on its structure, where energy flows from producer to end user in a fair way. This paper introduces a hierarchical energy trading framework, formulated as a three-stage Stackelberg game, to enhance SW. In the first stage of this hierarchy, the retailer, acting as the sole leader, seeks to maximize profits through optimized energy sales to charging stations (CS). Subsequently, in the second stage, each CS operates as a leader for EVs, aiming to maximize profits by minimizing energy trading costs, while also acting as a follower in response to the retailer's strategies. The third and final stage involves EVs collaboratively acting as a unified strategic agent to minimize their trading costs through optimized charging and discharging schedules. This paper also introduces an average price penalty function to further enhance SW in the energy market. The proposed model, addressing the complexities of energy trading interactions, is formulated as a non-linear optimization problem with constraints. It has been implemented in a Python environment and solved using the Gurobi optimization solver, demonstrating its potential to improve the efficiency, fairness, and overall social welfare of the energy trading market. • Introduces a hierarchical energy trading framework using a three-stage Stackelberg game to enhance market social welfare. • Incorporates renewable energy at the retailer level, diversifying energy sources and boosting ecological relevance. • Establishes comprehensive pricing functions across all levels, including reciprocal EV discharge signals, for dynamic market interaction. • Implements an average price penalty at charging stations to preserve social welfare and promote efficient energy use. • Demonstrates model efficiency and practical applicability through tests on the IEEE 33 bus system, showing superior profitability and convergence. [ABSTRACT FROM AUTHOR]

• Surveyed same retailers thrice; before, a month after and a year after the ban. • A month after; use of plastic bag reduced, reusable bag surged, no effect in total bag. • A year after; plastic bag reduced but not the reusable bag—total bag use reduced. • Expected fine and its effect reduced a year after the ban as compared to a month after. • Enforcing ban reduces plastic bag immediately, but reducing the total bag takes time. • Long term enforcement of ban can reduce the bag related waste in municipalities. Banning single-use plastic bags is a popular policy intervention among cities in developing countries such as Nepal. While the policy marks some success in curbing plastic bag usage, it confronts two major challenges. First, the effect of the ban often dilutes and becomes ineffective over time. Second, bag leakage could occur as customers switch to unregulated plastic bags and create more pollutants. Using three rounds of retailer-level panel data from the Dharan Municipality of Nepal, this study finds evidence to support both contentions. The usage of plastic bags slows down initially but rises subsequently as the subjective probability of being caught for using banned plastic bags reduces with time. One year after the ban, an increase in the expected fine does not increase the use of reusable bags but significantly reduces that of banned plastic bags. These results show that the ban does help reduce the total bag use in the short term but requires continued monitoring and enforcement to be effective in the long term. [ABSTRACT FROM AUTHOR]

Seafood has become one of the most heavily traded food commodities in the era of globalization. International seafood supply chains are complex and contend with many difficulties in bringing an enormous variety of products to market. A major challenge involves accurately labelling products such that they comply with a diverse set of regulatory frameworks, ranging from country-of-origin through to the final point of consumer sale. Thanks to DNA barcoding, seafood mislabelling is now recognized as a global problem, with potentially negative impacts on human health, economy and the environment. Mislabelling can result from species misidentification, use of inappropriate common names, incomplete and/or out-dated regulatory frameworks, or through market substitution. While prior studies have focused primarily on retail and food service establishments, this study used barcoding to assess rates of finfish mislabelling at multiple points in the supply chain within Ontario, Canada. A total of 203 specimens from 12 key targeted species were collected from varied importers, registered processing plants and retailers in Southern Ontario and identified using DNA barcoding. Species identity of samples was used to assess conformity of labelling against the Canadian Food Inspection Agency's (CFIA) Fish List, which revealed an overall mislabelling rate of 32.3% among targeted species. The mislabelling rate was significantly different between samples collected from importers and retailers. Among the mislabelled samples were seven samples that originated from US and were properly labelled according to US Food and Drug Administration (FDA) Seafood List. This study evaluated the integrity of chain of custody documents and identified discrepancies in 43 samples (21.4%). Implementing seafood traceability throughout the supply chain and harmonizing labelling regulations between countries can help to ensure industry compliance in a globalized market, while sampling at multiple points in the supply chain can help to reveal causes. Venn diagram showing the lack of harmonization between the CFIA and FDA seafood regulatory frameworks. The diagram was based on fish lists downloaded on December 8th, 2016. The figure was created by VENNY 2.1 tool (Oliveros, 2007). Oliveros J. VENNY. An interactive tool for comparing lists with Venn's Diagrams. http://bioinfogp.cnb.csic.es/tools/venny/index.html2007-2015. Unlabelled Image • Accurate labeling of seafood products is a major challenge. • A total of 203 seafood samples were collected at multiple points in the supply chain. • DNA barcoding revealed an overall mislabelling rate of 32.3%. • The mislabelling rate varied between samples collected from importers and retailers. • Discrepancies in chain of custody documents were observed for 43 samples (21.4%). [ABSTRACT FROM AUTHOR]

Electricity retailers desire to specify the energy acquisition strategy and selling prices in a way that maximize the expected profit, and convince consumers to choose them as the energy provider. Reducing selling price decreases retailers’ income, and vice versa. Moreover, the higher selling price increases clients’ switching probability to rivals that reduces the retailer’s expected income. Therefore, the retailer faces a tradeoff between selling prices and clients’ consumption. Additionally, fluctuations of wholesale prices, random demand, unexpected failures of self-generation facilities, and risk of rivals’ strategies are other difficulties faced by retailers, and these uncertainty resources affect their profits. This paper presents a fuzzy Information Gap Decision Theory (IGDT) based framework for electricity retailers to specify the energy acquisition strategy. Uncertainty of wholesale price is modeled via unknown bounded intervals. Additionally, the Point Estimate Method (PEM) is proposed to cope with the uncertainty of rivals’ strategies. Clients’ reaction to retail-selling prices is incorporated into the proposed framework via fuzzy numbers. In order to model the availability of generating units, a novel scheduling framework considering the repair time for failed units, in addition to repair cost and forced outage rate (FOR) is presented in this research. Finally, IGDT methodology is applied to determine the retailer’s energy acquisition strategy based on financial risk preferences. Performance of proposed model is evaluated via a case study, and the numerical results are discussed. [ABSTRACT FROM AUTHOR]

Aims: This study was undertaken to ascertain whether light occupational exposure to pesticides by retailers might be associated with any liver, kidney, nervous system dysfunction or hematological abnormalities. Main methods: In this cross-sectional study, 70 male pesticide retailers (cases) and 64 male subjects, randomly selected from the constructions workers of city council contractors, as the referent group, were investigated. Urine and blood samples were taken from all subjects for urine analysis, hematological and biochemical parameters. Data analysis was conducted through SPSS v.19 using t -test and chi-square test. Key findings: The results of urine analysis showed that the frequency of abnormal urine tests was significantly higher in cases than in referent individuals. Similarly, the results of CBC showed that the mean values of monocyte, hemoglobin, hematocrit, mean corpuscular volume, mean corpuscular hemoglobin and platelet distribution width were significantly lower, and mean corpuscular hemoglobin concentration and red blood cell distribution width were significantly higher in retailers. No significant differences were found for other parameters. Significance: These findings indicate that an association exists between exposure to pesticides by retailers and early subtle and sub-clinical changes in the urine tests and hematological parameters. Engineering measures are recommended to eliminate exposure to pesticides and to prevent its associated outcomes. [ABSTRACT FROM AUTHOR]

This paper proposes a robust midterm framework to determine optimal time-of-use (TOU) electricity pricing for retailers using intuitionistic fuzzy divergence based thresholding. It will analyze load profile and perform a comprehensive evaluation of load violation and uncertainty as well by exponential intuitionistic fuzzy entropy. The key advantage is that the proposed method will handle uncertain behavior of load and wholesale price with membership and non-membership functions. In the proposed algorithm client response to the retailer prices and the competition among rival retailers have been explicitly taken into account. The proposed scheme can be applied to several pricing policies where the peak-to-average ratio (PAR) will be decreased. The model is implemented on a realistic case in which the superior performance of the proposed method is demonstrated. [ABSTRACT FROM AUTHOR]

This paper investigates a bi-level stochastic energy acquisition strategy for electricity retailers with self-generation facilities to supply clients' demand from various resources of energy. The main propose of the presented work is modeling clients' switching behavior based on uncertainties of rival retailers' strategy and wholesale prices. The upper sub-problem models wholesale price fluctuations and determines retailer's participation levels in the forward and wholesale markets as well as scheduling of self-generation facilities based on the minimum supply cost. In the lower sub-problem, the Dempster-Shafer evidence theory (DSET) is applied to determine the retail selling price based on rivals' strategies and clients' switching tendency. DSET defines two belief and plausibility functions to evaluate the possibility of accepting selling prices by clients. According to the retailer's defined belief level and the minimum expected cost, the selling price is calculated in the lower sub-problems. Finally, a case study is used to show the performance of proposed method. [ABSTRACT FROM AUTHOR]

The food chain is intrinsically linked to agriculture and enables a transition towards a Circular Economy (CE) system and a resource efficient future. Accordingly, the development of analytical models appears particularly useful to address these challenges and to assess CE strategies. In this study, we develop a theoretical model to investigate the relationship between market structure and food waste. We consider an oligopolistic market with N differentiated firms (retailers), where each firm sells a final perishable good (food) in a context of strategic interaction. We use this model to analyse and compare two policy instruments aimed to reduce food waste, namely taxation and circular economy approach. The social welfare index, given by the sum of firms' profits and consumers' utility (surplus), is used to make this comparison. Food waste is an endogenous consequence of the interaction between competing retailers and consumers; interestingly, theoretical results suggest that the individual retailer's food waste is positively correlated with market concentration and the quality of goods. In general, circular economy shows a higher welfare than taxation especially when customers are particularly sensitive to the amount of goods available on the shelves. The study is completed by numerical simulations. [Display omitted] • Oligopoly model developed to analyse two policy instruments aimed to reduce FW. • Social welfare index is used to make this comparison. • FW is positively correlated with market concentration and the quality of goods. • CE shows a higher welfare than taxation. [ABSTRACT FROM AUTHOR]

Government of India, to help the small scale retailers especially to promote the growth of unorganized retail sector introduced a software called eGalla. This is a Retail Management System (RMS), with low installation charges and is aimed to help the local retail shops to face the challenges possessed by big players in the market. However, two years since its launch the product gained limited attraction and shopkeepers hardly use it. This study aims to understand the marketing strategies employed by other products in the same domain and also identifies the gaps in the existing software. Shopkeepers using different RMS were interviewed using a questionnaire. The study captured satisfaction level achieved for various attributes of the product and also for the promised benefits. The study also discuss the initial set up cost, training time, changes that the software brought in and the increment in sales that happened after the software installation. The study identified a few missing modules which were of high demand among the existing users of similar software and recommends solutions to overcome these challenges based on the users experience with other software. [ABSTRACT FROM AUTHOR]

This paper reports on a landmark study to field-test the influence of a large retailer to change the behaviour of its millions of customers. Previous studies have suggested that social media interaction can influence behaviour. This study implemented three interventions with messages to encourage reductions in food waste. The first was a social influence intervention that used the retailer’s Facebook pages to encourage its customers to interact. Two additional information interventions were used as a comparison through the retailer’s print/digital magazine and e-newsletter. Three national surveys tracked customers’ self-reported food waste one month before as well as two weeks after and five months after the interventions. The control group included those who said they had not seen any of the interventions. The results were surprising and significant in that the social media and e-newsletter interventions as well as the control group all showed significant reductions in self-reported food waste by customers over the study period. Hence in this field study, social media does not seem to replicate enough of the effect of ‘face-to-face’ interaction shown in previous studies to change behaviour above other factors in the shopping setting. This may indicate that results from laboratory-based studies may over-emphasise the effect of social media interventions. [ABSTRACT FROM AUTHOR]

This research explores logistics-related leverages in the responsibility of retailers for improving the environmental performance of a Fast Moving Consumer Goods (FMCG) distribution network. We examine opportunities for modifying the network carbon footprint by changing network design variables. To do so, a quantitative distribution network model is established, and 150 scenarios are calculated by modifying real-world shipment data from an existing multinational FMCG manufacturer. Four distribution variables are identified for a many-to-many and a hub-and-spoke network structure. Two variables affect the distribution network and two interfere in the shipment structure by manipulating weight and/or the delivery date. This research sheds light on the extent of the changes in greenhouse gas (GHG) emissions of the distribution network that result from modifications in the logistics variables. The greatest effect on the quantity of GHG emissions can be observed when an anticipation horizon for orders is introduced. When shipments are consolidated and delivered only weekly or biweekly from the manufacturer to the retailers, GHG emissions drop significantly. Another opportunity for retailers to cut down GHG emissions is based on the concept of minimum order quantities where shipments to a retailer location are bundled until a certain weight is reached. Additionally, total GHG emissions of distribution may be reduced by raising the tonnage limit, thereby triggering direct shipments between the manufacturer’s facilities and the retailer locations, or by raising the tonnage limit, which triggers direct shipments in the logistics service provider network. The extent of GHG reduction is assessed for all investigated variables. [ABSTRACT FROM AUTHOR]

This paper addresses the deciding under uncertainty of an electricity retailer in order to maximise its total expected rate of return. The developed methodology is based on the modelling of the stochastic evolution of zonal prices that seeks to manage a portfolio of different contracts. Retailer's load and the price at each zone are forecasted using the seasonal autoregressive integrated moving average (SARIMA) model and a clustering technique is used for scenario reduction. Supply sources include the pool, self-production facilities, forward and bilateral contracts. The risk of cost fluctuation due to uncertainties is explicitly modelled using the multi-scenario drawdown methodology. This risk function quantifies in aggregated format the frequency and magnitude of the portfolio drawdowns over planning horizon. In-sample and out-of-sample runs are performed for a portfolio allocation problem. Carried out experimental results on the basis of realistic data, show that imposing risk constraints improve the “real” performance of a portfolio management in out-of-sample runs. [ABSTRACT FROM AUTHOR]

• The influence of POP type on shape abnormality perception and purchase probability is studied. • The moderating role of shape type (i.e., abnormality level) in the relationship POP type – abnormality perception is studied. • Romanian consumers' misshapen tomato abnormality perceptions are lowest in fresh markets. • UK consumers' misshapen tomato abnormality perceptions are lowest in organic supermarket stands. • POP can be a 'decision point' for retailers regarding misshapen fruits and vegetable markets. The present study endorses the point of purchase (POP) as a 'decision point' for the distribution of misshapen fruits and vegetables (FVs) and a contributor to reducing food waste. We have explored the influence of POP type on consumer perceptions of tomato shape abnormality and its purchase probability, and the moderating role of the actual tomato shape abnormality level. Two online surveys questioned a total of 1021 Romanian and British consumers. The results show that consumers perceive misshapen tomatoes as 'least misshapen' and 'most likely to be bought' in fresh markets (Romania) or the organic stand of the supermarkets (UK). This study provides managerial recommendations on the selection of point of sale for misshapen fresh FVs with the aim of addressing the problem of food waste. [ABSTRACT FROM AUTHOR]

This paper presents a novel electricity retail market model in which elastic demands of consumers in a distribution network are traded at flexible selling prices offered by a retailer. The main works of this paper are in three points: (1) Flexible and divided selling price settings over one day by the retailer, (2) flexible and elastic responses corresponding to the selling prices (price-based Demand Response: DR) by different types of consumers, and (3) distribution network physical constraints to obtain the realistic cost of tariff for usage of the distribution network imposed to the retailer are formulated. Unlike previous related works, the proposed model is a new one applicable to the behavior analysis of decision makers in the deregulated environment with such flexible transactions. In the transactions, the retailer offers a selling price for a unit time period over one day and the consumers elastically respond to the prices. Assuming that the consumers respond to the prices rationally and control their demands flexibly, we model the transaction as a Stackelberg game formulated by a bi-level programming problem. The behavior of the market players is examined in computational experiments using the spot price data in Japan Electricity Power eXchange (JEPX) and distribution network models, i.e. modified IEEE 13 bus test system model and IEEE 33-bus radial distribution test system model. We employ a genetic algorithm to find an approximated solution of the formulated non-convex bi-level programming problem. The computational results show some new findings about the deregulated retail market if flexible transactions between the retailer and the consumers are realized. [ABSTRACT FROM AUTHOR]

A range of new models is available for power system restructuring in India to meet the requirements of state and central government policies as well as the social and market needs of the state. Uttar Pradesh Power Corporation Limited provides a useful case study of these possibilities. [ABSTRACT FROM AUTHOR]

Forecasting errors in a power system occasionally leads to situations where either production or consumption is required to be altered. In order to improve demand-side contribution under these special conditions, this paper introduces an intra-hour control strategy that allows a retailer to request regulating power from flexible loads. The load under research is electric storage space heating (ESSH) employing model predictive control (MPC) for minimizing the heating cost and ensuring customer comfort. In the proposed framework, a regulation request is sent to the loads, after which they solve the price and volume of their regulation bids and communicate the bids back to the retailer. Centrally, the retailer aims to minimize prediction error costs by finding the cheapest mix of buying regulation from the loads and settling the error later in the imbalance settlement. The proposed control strategy is tested and evaluated in dynamic simulations. The results indicate that the thermal storages can be regulated by the proposed strategy and some savings in imbalance costs are possible. [ABSTRACT FROM AUTHOR]

In this paper, we formulate the electricity retailers’ short-term decision-making problem in a liberalized retail market as a multi-objective optimization model. Retailers with light physical assets, such as generation and storage units in the distribution network, are considered. Following advances in smart grid technologies, electricity retailers are becoming able to employ incentive-based demand response (DR) programs in addition to their physical assets to effectively manage the risks of market price and load variations. In this model, the DR scheduling is performed simultaneously with the dispatch of generation and storage units. The ultimate goal is to find the optimal values of the hourly financial incentives offered to the end-users. The proposed model considers the capacity obligations imposed on retailers by the grid operator. The profit seeking retailer also has the objective to minimize the peak demand to avoid the high capacity charges in form of grid tariffs or penalties. The non-dominated sorting genetic algorithm II (NSGA-II) is used to solve the multi-objective problem. It is a fast and elitist multi-objective evolutionary algorithm. A case study is solved to illustrate the efficient performance of the proposed methodology. Simulation results show the effectiveness of the model for designing the incentive-based DR programs and indicate the efficiency of NSGA-II in solving the retailers’ multi-objective problem. [ABSTRACT FROM AUTHOR]

Category management according to Dupre-Gruen (2004) links, while using low cost and differentiation to defend market position. The main motivation why we apply category management in retail trade (i.e. in a stone or electronic shop) is primarily profit maximization. For all stakeholders - producers, traders and consumers presents a number of benefits, even if that requires long-term planning and the results are visible only after a delay. The aim of this paper is an examination of the benefits of stakeholders, generalization of research findings category management in e-commerce and submission new categories that will increase the profitability of this business. [ABSTRACT FROM AUTHOR]

This paper proposes an economic instrument designed to assess the competitive nature of the sugar industry in Romania. In the first part of the paper is presented the theoretical background underlying index (HHI) and its calculation methodology. Then comes the results of a first application of this index for a total of 10 plants in the sugar industry, the robustness of these results is discussed. We believe HHI is a proactive tool that may prove useful competition authority, in its pursuit of continuous monitoring of various industries in the economy and in the internal decision-making on resource allocation institution (Peacock, and Prisecaru, 2013).The starting point of our research is to free competition in the European market with competitors much stronger than Romanian plants, plants that produce at a price lower than the domestic ones. In our study we will see if it is a concentration of production in factories around the strongest in Romania, concentration accompanied by the collapse of those who could not resist the market.The market concentration, competition policy, we will follow using the HHI index, for evaluation of impact analysis on existing trade, the number and size of competitors, protecting existing sales structures, avoiding disruptions in the competitive environment, etc. [ABSTRACT FROM AUTHOR]

In midterm planning, the objective of an electricity retailer is to manage a portfolio of different contracts and to determine the selling price offered to its clients. This paper provides a novel technique based on Information Gap Decision Theory (IGDT) to assess different strategies for a retailer under unstructured pool price uncertainty. This method can be used as a tool for assessing the risk levels, considering whether a retailer is risk-taking or risk-averse regarding its midterm strategies. Supply sources include forward contracts, a limited self-generating facility, and the pool. It is shown that in robust strategy, procurement from sources with uncertain prices decreases. Also, the selling price offered to the consumers rises, decreasing the actual demand of the retailer, and consequently the expected profit is decreased. A case study is used to illustrate the proposed technique. [ABSTRACT FROM AUTHOR]

Highlights: [•] We design network for an entrant SC which is supposed to compete an existing SC. [•] The rival SCs compete dynamically in markets with price and distance dependent demands. [•] During the SC strategic network design we also consider operational competition factors. [•] We design an exact algorithm and a heuristic algorithms to validate and solve large scale problems. [•] The model is test on random samples, applied to a real-life case and sensitivity analysis are provided. [Copyright &y& Elsevier]

Highlights: [•] The financial risk of the market price uncertainty is modelled using expected downside risk in the stochastic framework. [•] Roulette wheel mechanism and Lattice Monte Carlo Simulation are employed for random scenario generation. [•] The proposed optimization problem is solved by a decomposition technique using Benders decomposition algorithm. [ABSTRACT FROM AUTHOR]

Abstract: Retailers claim that they provide the products that consumers want but there is a much more complex dynamic process underpinning this relationship than the idea of consumer sovereignty. The paper explores this retailer–consumer relationship by considering how a variety of retailer activities influence consumers’ food preferences and choices and how innovation from the retail sector changes this relationship. Retailers influence food choice through the distribution formats they create and the ways they operate them. As new distribution formats are developed, both in home and foreign markets, the choices of food that are offered to consumers are changed. The retailer decides on the items to be displayed for sale and how these items are merchandised into product ranges and categories. Branding is an integral part of this sales activity, with retailers increasing their control over branding of food and grocery products and in so doing often determining the composition of the products offered to consumers. Within the environment of the food outlet the retailer can influence consumer choice through pricing and promotional activity. The pattern of mutual influence of retailer and consumer is extremely dynamic being driven by competitive innovation by the retailer rather than only consumer sovereignty. Retailers measure success in terms of increased sales and market share. Influencing what consumers buy is part of the competitive weaponry of large retailers and their tactics become more sophisticated as they succeed and become bigger. Examples are used to illustrate this pattern of influence on consumer choice and its dynamic nature. Whilst successful retailers undoubtedly respond to consumer demand they also are a major influence in shaping food choice and preferences – an influence that is likely to become more powerful over the next decade. [Copyright &y& Elsevier]

Abstract: Store brand plays a vital role in the success of retailers. Perceived quality is one of important factors influencing consumers’ store brand purchase intention. Store brand perceived quality is lower compared with objective quality or national brand. For this end, the purpose of this article is to examine how to manage store brand perceived quality in strategic level. This article firstly discusses how consumers evaluate product quality, and the theoretical background of the reason that store brand perceived quality is lower from the view of cue related theories. Then, consumers’ store brand quality evaluation is explored. Finally, this article presents several strategic tactics to increase store brand perceived quality. These tactics include choosing store''s name as store brand name, making large advertising investment, improving store brand product package, and strengthening the relationship with store brand product suppliers. [Copyright &y& Elsevier]

Abstract: This paper presents a new method to determine the optimal demand function for a retailer in power markets. It assumes that the retailer purchases the energy from either the day-ahead or the regulation market and sells it to the end users through fixed and/or real-time pricing contracts. The load is assumed to be price sensitive and the retailer to be price-taker. Through participation in the market and managing its risk, the retailer attempts to maximize its profit. The proposed method is tested on a typical power market. [Copyright &y& Elsevier]

• A new multi-objective framework is presented for electricity retailers. • The selling price is calculated based on profits of electricity retailer and customers. • Normalized normal constraint methodology is used to generate the Pareto frontier. The electricity retail market provides a marketplace for domestic consumers and retailers to buy and sell electricity in a competitive environment. Permitting final consumers to choose electricity retailers promotes suppliers' pluralism and clients' freedom, which leads to improvements in the quality of electricity retailing service. The main aim of a retailer and consumers is profit maximization, which highly depends on retail-selling price. Retailer's profit may be explicitly reduced by decreasing retail selling-price or implicitly reduced by increasing retail selling-price as increasing these prices may decrease clients' consumption. Accordingly, the retail selling-price, retailer energy procurement strategy, and clients' consumption should be simultaneously analyzed from the viewpoints of retailer and clients. In this paper, a multi-objective optimization problem is introduced to obtain the retailer's energy procurement strategy in terms of the profits of energy buyers and sellers. Moreover, the normalized normal constraint method as a proficient multi-objective optimization technique is utilized to solve the proposed multi-objective optimization problem determining the retailers' energy procurement strategy and retail selling-prices. Since the wholesale energy price is a highly volatile uncertainty source affecting the retailer's profit, the point estimate method is utilized to characterize the uncertainty of the wholesale energy price. Simulation results illustrate the effectiveness of the proposed non-deterministic multi-objective optimization problem. [ABSTRACT FROM AUTHOR]

Abstract: In an electricity market, the retailer sets up contracts with the wholesale side for purchasing electricity and with the customers for its selling. This paper proposes a mathematical method based on mixed-integer stochastic programming to determine the optimal sale price of electricity to customers and the electricity procurement policy of a retailer for a specified period. The retailer has multiple choices for electricity procurement, such as spot market, forward contracts, call options and self-production. Risk is considered and modeled by conditional value-at-risk methodology. Also, the competition between retailers is modeled using a market share function. A case study is illustrated to demonstrate the capability of the proposed method. [Copyright &y& Elsevier]

This paper discusses the optimal selling price and energy procurement strategies for a retailer in an electricity market [Electric Power Syst. Res. 79 (2009) 246-254] while the optimal strategy of a retailer over a time period is presented to decide on the optimal energy purchase portfolio from several sources. The risk is assessed using linearized Conditional Value at Risk (CVaR) while CVaR is considered with the coherency properties (translation invariance, sub additivity, positive homogeneity and monotonicity). Indeed, CVaR lacks the monotonicity property. Therefore, this paper intends to prove this issue. [ABSTRACT FROM AUTHOR]

• The reception of personalization of Mobile Commerce and associated challenges was studied. • The security concerns and potential risks impact the use of retail services, smartphone usage and privacy. • Low bandwidth of mobile internet and network connectivity issues are associated with MC personalization. This study investigates the reception of personalization of Mobile Commerce (MC) and its associated challenges. A specific focus has been given to the elements that influence client's satisfaction. The study adopts a quantitative study design in which data was collected through a survey conducted on 340 Mobile Commerce consumers. Data have been analysed through Pearson correlation, KMO and Bartlett's test, multiple regression analysis, and factor analysis. The findings of the analyses depict that security concerns and potential risks impact the use of retail services (correlation coefficient, 0.915; P< 0.05), and smartphone usage and privacy (correlation coefficient, 0.891; P< 0.05). Moreover, security hazards have been identified as the primary factor that influences the adjustment of Mobile Commerce administrations. The study findings are significant as they can be used to bring about improvements in the existing Mobile Commerce-based services that will lead to the increase in the customer satisfaction level and expansion of the loyal customer base. Image, graphical abstract [ABSTRACT FROM AUTHOR]

As a high value commodity on the market, extra virgin olive oil (EVOO) is a suitable target for fraudsters. To understand differences in perceived fraud vulnerability between tier groups across the EVOO supply chain and to disclose underlying factors, the perceived fraud vulnerability of 28 companies was examined using the SSAFE food fraud vulnerability assessment tool. Amongst these companies were seven olive oil producers, seven business-to-business (B2B) companies, seven food manufacturers and seven retailers. The similarities and differences in perceived fraud vulnerabilities according to group characteristics (the role, the scale and the location of the company) were evaluated. Non-parametric tests and multiple correspondence analysis were applied for data exploration. An in-depth fraud vulnerability assessment of the EVOO supply chain was provided. Eight fraud factors related to opportunities and motivations scored high in the supply chain indicating their importance as fraud drivers and enablers. Four factors related to control measures are perceived as greatest vulnerability in the EVOO supply chain. Then, the vulnerability to fraud in the EVOO supply chain across all actors is perceived as high level on average. In decreasing contribution to the overall perceived fraud vulnerability, the fraud factor categories were ranked as follow: technical opportunities, a lack of managerial controls, a lack of technical controls, economic drivers, cultural and behavioural drivers, and opportunities in time and place. Among the tier groups, the retailers and B2B companies experienced higher levels of perceived vulnerability than olive oil producers and food manufacturers due to the additional vulnerability related to the opportunities in time and place, and greatest lack of control measures. Furthermore, the perceived fraud vulnerability of the company was not only determined by the tier group, but also impacted by the scale and location of the company. • EVOO supply actors differ considerably in fraud vulnerability. • Key vulnerability factors are simple adulteration, detection difficulty and lack of monitoring systems. • Retailers and B2B companies perceive themselves as more vulnerable to fraud than other actors. • Perceived fraud vulnerability is also affected by scale and location of the actors. [ABSTRACT FROM AUTHOR]

The food waste problem is not simple and it requires the integration of various actors involved in the food supply chain. Otherwise, the goal of reducing food waste and minimizing the negative environmental, social, and economic consequences would be difficult to attain. Up to now, far too little attention has been paid to understanding the food waste factors at the downstream stages of the food supply chain. This critical systematic review aims to identify the potential causes of food waste at the downstream entities of the food supply chain and provides a coherent and integrated knowledge basis of these factors. A configurative systematic literature review has been performed and after a filtering process, 92 articles were analyzed and synthesized. The potential factors were identified and categorized into three groups as (i) internal, (ii) micro-environmental, and (iii) macro-environmental. The factors suggest that the food waste problem critically depends on an organization's activities and is influenced by micro- and macro-environmental elements. Finally, the review discusses contradictory findings and provides future research avenues. Image 1 • Food waste factors across the downstream entities of the supply chain were determined. • 92 articles from WoS database were reviewed to analyze the factors causing food waste. • The causes of food waste were synthesized into three factors. • Food waste factors differ based on the downstream entity's type. • Knowledge gaps and future research directions are presented. [ABSTRACT FROM AUTHOR]

The final step that Portugal is taking to reach a fully liberalized electricity market is the deregulation of the retail market by phasing-out regulated electricity prices and reducing the administrative burdens in this area. These attempts are done to promote the entrance of companies into the retailing business and to actively engage the end-users in the market. This analysis shows that despite high consumer switching rates during the 2013–2015 period, the retail market in Portugal is still highly concentrated. The retail rates are also not following the changes in the wholesale market price. [ABSTRACT FROM AUTHOR]

• Investigation of interaction between market trading strategies and the behavior of household appliances. • Discussion about the role of schedulable household appliances in secure operation of the distribution network. • Determination of retail strategies in the market based on household behavior considering electricity price uncertainties. In this paper, a novel approach is proposed to optimize the behavior of household appliances towards retail electricity price. At the supply-side, a distributed generation-owning retailer participates in the wholesale electricity market, i.e. day-ahead and intraday trading floors. Considering the uncertainties associated with electricity price and wind/solar power, the retailer determines the retail price using stochastic programming. At the demand-side, smart household prosumers take the advantage of two kinds of storage capacities: (1) thermal storage capacity of thermostatic devices and (2) electrical storage capacity of batteries integrated with roof-top photovoltaic panels. The Home Energy Management System (HEMS) determines the operational strategies of appliances, including thermostatically controlled, uninterruptible and curtailable appliances, in response to the retail price. The HEMS uses a heuristic Forward-Backward Algorithm (F-BA) to minimize the energy cost of the thermal appliances satisfying the residents' comfort. To prevent from creating peak demands in the power system, a Peak Flattening Scheme (PFS) is suggested. Investigating the interaction between household consumption and network security, the household demands are located at different buses of a distribution network relieving congestion in weak lines. Finally, the proposed approach is implemented as a case for Danish sector of Nordic Electricity Market. [ABSTRACT FROM AUTHOR]