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China is the most productive seaweed farming country in the world and her seaweed imports and exports have a significant impact on global seaweed trade commodities and food security. Nevertheless, few studies had delved into the main characteristics and development of China's seaweed farming industry. This paper aims to narrow this research gap by analyzing trade patterns in China's seaweed products and the international competitiveness of seaweed product by using the international market share index (IMS), the trade competitiveness index (TC), and revealed comparative advantage index (RCA) from 2002 to 2017. The results showed that Japan, the Association of Southeast Asian Nations (ASEAN), Chile, Peru, and the Republic of Korea are China's main trade partners, the total trade value of China's seaweed products has grown rapidly, its imports have gradually exceeded exports, the trade deficit continues to expand, and its competitiveness keeps decreasing. The reasons for this trend may include the changing seaweed trade commodity structure, product differentiation, increased government support in competing countries, and trade barriers among the trade partners. We propose actively expanding international trade markets, establishing a strong seaweed product processing industry to develop high value-added seaweed products, optimizing the trade commodity structure, and differentiating of seaweed products to improve the competitiveness of China's seaweed products.

Mediterranean mussel farming in Greece developed considerably during the last 40 years reaching a gross commodity product up to the limits of the country's production capacity (35–40,000 tonnes/year). Despite the achievements in the sector's growth, little or no effort has been attributed yet to risk assessment and moreover to risk management of the activity. The present effort aims at developing a working framework for the shellfish aquaculture of Greece to be used as a tool by the sector's decision makers to advance strategies for risk elimination or avoidance. The work was based on a generic risk management standard tool, the Joint Australian and New Zealand Risk Management Standard AS/NZS ISO 31000:2009 that has been adapted to the specific national characteristics of all levels of the mussel farming business -activities and the industry function. The framework supported by data sets regarding development, production, profits and losses, retrieved by surveys through distributed questionnaires or interviews during site-visits, as well as by collecting data from national and international authorities. Data input covered technology, farm size, farmer risk-attitude, risk-management strategies, risk-perceptions and socioeconomic profiles. Major risks and risk management options were identified providing aid for remediation risk policies to the stakeholders.

We examine the effectiveness of a quality assurance mechanism that relies on a third-party’s reputation. We focus on the market for fine and rare wines where auction houses intermediating between sellers and buyers have also claimed expertise to assess product authenticity. An auction house’s reputation can sustain product quality in this market only if consumers absorb relevant information and punish houses who fail at screening out counterfeits. We test the existence of such reputational effects by studying the market responses to two disclosures of houses having auctioned fake wine. We find that one house experienced negligible losses after a 2008 event involving a limited number of counterfeit bottles. However, three houses associated with a 2012 incident involving thousands of bottles are found to have suffered reputational losses. These losses are demonstrated over the following year by an average 4.5% decrease in equilibrium sales prices of all wines, and a slight decrease in sales quantities of older wines, relative to other houses.

To maximize productivity, manufacturers must organize and equip their workforces to efficiently handle variable workloads. Their success depends on their ability to assign experienced and skilled workers to specialized tasks and coordinate work on production lines. Worker turnover may disrupt such efforts. We use staffing, productivity, and pay data from within a major consumer electronics manufacturer’s supply chain to study how firms should manage worker turnover and its effects using production decisions, wages, and inventory. We find that worker turnover impedes coordination between assembly line coworkers by weakening knowledge sharing and relationships. Publicly available unit-cost estimates imply that worker turnover accounts for $206–274 million in added direct expenses alone from defectively assembled units failing the firm’s stringent quality control. To evaluate managerial alternatives, we structurally estimate a dynamic equilibrium model (an Experience-Based Equilibrium) encompassing (1) workers’ endogenous turnover decisions and (2) the firm’s weekly planning of its production scheduling and staffing in response. In counterfactual analyses, a less turnover-prone, hence more productive, workforce significantly benefits the firm, reducing its variable production costs by 4.5%, or an estimated $928 million for the studied product. Such benefits justify paying higher efficiency wages even to less skilled workforces; furthermore, interestingly, rational inventory management policies incentivize self-interested firms to reduce rather than tolerate turnover. This paper was accepted by Vishal Gaur, operations management. Funding: The authors gratefully acknowledge support from the data sponsor, and K. Moon gratefully acknowledges support from the Wharton Dean’s Research Fund and the Claude Marion Endowed Faculty Scholar Award of the Wharton School. Supplemental Material: The online appendices are available at https://doi.org/10.1287/mnsc.2022.4476 .

Motivated by the practices of production sourcing in the apparel manufacturing industry, this article investigates an apparel manufacturing supply chain wherein an original brand manufacturer (OBM) may either outsource production to a competitive manufacturer (CM) or a non-CM (NCM) or set up factories to produce in-house, namely, Strategy C, Strategy NC, and Strategy N, respectively. If the OBM outsources production to the CM, technology spillover happens, and the CM is able to manufacture products with the same consumers’ preference level as the OBM does. We find that the OBM prefers Strategy N regardless of the manufacturing level and consumers’ product preference level when the investment cost is low. However, the OBM prefers Strategy C or NC when the investment cost is high. Specifically, when the manufacturing level is high, or the manufacturing level is medium, and the consumers’ product preference level is high, the OBM prefers Strategy NC; otherwise, the OBM prefers Strategy C. Furthermore, we demonstrate that employing the dual-sourcing strategy wherein the OBM outsources production to both CM and NCM simultaneously does not necessarily help OBM effectively mitigate the negative impact of technology spillover and delivery uncertainty, which depends on specific conditions.

Motivated by the practices of technology investment in the new energy vehicle manufacturing industry, this article investigates an outsourcing supply chain in which an original brand manufacturer (OBM) possessing the core new energy technology R&D outsources production to a competitive manufacturer (CM). To cater to market demands and increase market competitiveness, the CM may actively invest in technology with the OBM or by himself, or not, i.e., Strategies JI, OI, and NI, respectively. In particular, owing to technology spillover effect, the CM could use the technology inferior to the OBM's to produce his own-branded products in Strategy NI. Our results reveal that the OBM consistently profits the most in Strategy JI. However, the CM's preference strategy is influenced by the competition intensity, technology spillover level, consumers’ product preference, and cost-sharing ratio. In specific, when both the competition intensity and technology spillover are weak or the competition intensity is strong for arbitrary technology spillover level, the CM may prefer Strategy JI or OI depending on consumers’ product preference and cost-sharing ratio and never prefers Strategy NI. However, when the competition intensity is weak but the technology spillover level is strong, the CM may prefer Strategy NI in certain situations. Furthermore, our study extends the model to involve variable production costs, and reveals that the main results derived in the basic model still hold.

Sensory nudge has been creating a significant impact in the field of market research with implementation of methods used in neuro marketing. These methods help in understanding the impact of sensory nudge on consumer purchase behavior. This research paper focuses on the impact of different sensory nudges due to the packaging, promotional activities, design and other motivational that influences the purchase behavior for green product. This sensory nudge stimulates the environmental consciousness of the consumers and their preference for green products over conventional products. This research work has been started with an introduction to the research topic followed by an extensive review of literature related to the subject matter. Then the conceptual framework for the study was developed followed by research hypotheses. The testing of hypotheses was carried by using specified research methodology with the help of a structured questionnaire for conducting the survey. The results from data analysis were interpreted. The major challenge in this context is to know the impact of sensory nudge derived from marketing activities that modulate consumer’s perception, attitude, and behaviour towards purchasing of green products that builds environmental sustainability. Based on the extensive review of the literature, this study addresses the causes that restrict consumers’ from using green products. This study also scrutinizes the environmental consciousness of the respondents. The research work includes analyzing the awareness level of green products and perception about the term green.

In the agriculture and healthcare industries, AI has been deployed to achieve better crop production, disease prediction, continuous monitoring, efficient supply chain management, improved operational efficiency, and reduced water waste, with the main goal of designing standard, reliable product quality control methods and the search for new ways of reaching and serving society while maintaining low cost. Machine learning and deep learning are two of the most often used AI approaches. Individuals, businesses, and government agencies utilize these models to anticipate and learn from data. Machine learning models for the complexity and diversity of data in the real-world applications are being developed at the moment. This article discusses machine learning and artificial intelligence applications in agriculture, healthcare, management, and social studies. Disease Prediction, water irrigation optimization, Sales growth, profit maximization, sales forecast, inventory management, security, fraud detection, and portfolio management are some of the major uses.

In the agriculture and healthcare industries, AI has been deployed to achieve better crop production, disease prediction, continuous monitoring, efficient supply chain management, improved operational efficiency, and reduced water waste, with the main goal of designing standard, reliable product quality control methods and the search for new ways of reaching and serving society while maintaining low cost. Machine learning and deep learning are two of the most often used AI approaches. Individuals, businesses, and government agencies utilize these models to anticipate and learn from data. Machine learning models for the complexity and diversity of data in the real-world applications are being developed at the moment. This article discusses machine learning and artificial intelligence applications in agriculture, healthcare, management, and social studies. Disease Prediction, water irrigation optimization, Sales growth, profit maximization, sales forecast, inventory management, security, fraud detection, and portfolio management are some of the major uses.

The product recall is becoming a challenging issue in supply chain management, and both suppliers and manufacturers are motivated to exert recall efforts to improve supply chain performance. Considering a supply chain composed of one supplier and one manufacturer with product recalls and demand uncertainty, we investigate the contract design by integrating the revenue sharing contract with three cost sharing policies, namely, fixed-rate cost sharing (Contract F), linear cost sharing (Contract L), and threshold-based cost sharing (Contract T), to coordinate the production quantity and recall efforts. Results show that cost sharing could improve the product recall probability and supply chain profits, but only Contract T can coordinate the supply chain in both production quantity and recall efforts. Moreover, the cost sharing rate in Contract T first decreases and then increases as the recall cost increases. When the recall cost is small (large), Contract T (Contract F) is optimal for the manufacturer. In contrast to our intuition, we find Contract L could overmotivate supply chain members to exert a recall effort that is greater than the first-best when the cost coefficient of recall efforts is large enough. However, demand uncertainty will mitigate the impact of product recalls on motivating recall efforts.

In the e-commerce and financial industries, AI has been deployed to achieve better customer experience, efficient supply chain management, improved operational efficiency, and reduced mate size, with the main goal of designing standard, reliable product quality control methods and the search for new ways of reaching and serving customers while maintaining low cost. Machine learning and deep learning are two of the most often used AI approaches. Individuals, businesses, and government agencies utilize these models to anticipate and learn from data. Machine learning models for the complexity and diversity of data in the food industry are being developed at the moment. This article discusses machine learning and artificial intelligence applications in e-commerce, corporate management, and finance. Sales growth, profit maximization, sales forecast, inventory management, security, fraud detection, and portfolio management are some of the major uses.

In this article, we study a multiproduct multiperiod production planning problem faced by a cash-strapped manufacturer, who utilizes inventory-based financing (IBF) to capture additional demand during peak season, which otherwise will not be met due to cash shortage. Each product has a unique selling season and its production incurs a significant setup cost. We formulate the problem as an integer program and show the special case with one product is NP-hard. By exploiting the inherent structure of three distinct but related decisions, i.e., the production, financing, and working capital allocation decisions, we develop a Lagrangian relaxation-based branch-and-bound procedure to solve the model. Through a series of numerical experiments using real data, this article presents managerial insights into how the manufacturer's optimal production plan could differ with and without IBF. In an optimal plan, we show the profit maximizing strategy for the cash-strapped manufacturer is to overstock and pledge inventories to secure more loans prior to peak demand periods.

Military technologies are typically the product of long-term development efforts. These technologies are often adapted late in the development process for use by other users, including other members of the defense enterprise, foreign militaries, or the commercial sector. The need to adapt a technology can arise from cost over-runs or changing operational requirements. This article describes a value-based methodology for developing a transition plan early in the development process, when the system is still in the conceptual phase. Performing this analysis early in the design phase allows for design choices that will support adapting the system for other users. Moreover, it provides a risk mitigation strategy against cost over-run and changes in operational requirements. The process begins by capturing the functional architecture of the technology and analyzing them against a set of tasks associated with different military positions. From there, the adapted technology is evaluated for its projected adequacy based on the value added and the effort required for adaptation. The end-state of this analysis is a value-based model that identifies a portfolio of possible alternative markets and/or uses, which can be comparatively analyzed. A case study is presented for adapting a military augmented reality system for a different market.

This article considers a two-stage supply chain consisting of a supplier and two competing multichannel retailers and examines their channel and pricing strategies. The supplier wholesales a product to the retailers who resell the product to consumers with different channel preferences. The retailers can either operate their online and offline channels separately and apply differential pricing strategy, or choose to integrate the channels and adopt unified pricing strategy. We establish a game-theoretical model to derive the optimal wholesale price of the supplier and equilibrium retailing prices of the two retailers, and investigate the impact of consumer structure and channel integration ability on the prices, demands, and profits. We then analyze the effect of channel integration and discuss the equilibrium strategy. We find no adoption, asymmetric adoption, and symmetric adoption of channel integration strategy are all possible equilibria. However, one or the both retailers can be worse off in the competition, while the supplier can be always better off if any retailer integrates the channels. Our results suggest that retailers should be very cautious when deciding whether to integrate channels under competition, and the supplier could design other mechanisms to encourage the retailers to integrate their channels.

We study an online game supply chain that is composed of a game developer and a distributor. We investigate the impact of the distributor sharing demand information on the game quality investment during the game development stage and the marketing investment. Our analyses show that information sharing does not always improve marketing investment. When the online game market demand is relatively insensitive to the game price, sharing information motivates the distributor to invest more in marketing. In addition, information sharing always affects the developer's decision in product quality. The developer will be less conservative in product quality when it is more certain about the market demand and commit a higher investment after having demand information shared with it. For the distributor, we find that information sharing only results in a higher markup decision when the market demand is not very sensitive to the game price. There exists a Pareto improvement region so that the distributor will voluntarily share the demand information, which benefits both supply chain members.

It is important for marketing academics and public policymakers to understand how to persuade consumers to consume healthier food instead of unhealthy food. Based on the theories of synchrony effect and self-control, this research makes novel predictions about the time-of-day effects on (un)healthy food purchases. The results of a field study and a laboratory experiment confirm that consumers’ self-control level becomes lower in the evening, which leads consumers to buy more unhealthy products in the evening than they do in the morning. A follow-up eye-tracking experiment reveals the underlying mechanism through which self-control failure makes consumers pay more visual attention to unhealthy food and the weaker effect of attention to healthy food on purchases. The results of this study provide valuable insights not only for marketing academics but also for retailers and consumer marketing companies.

This paper explores how social interactions among consumers shape markets. In a two-country model, consumers meet and exchange information about the quality of the goods. As information spreads, the demands evolve, affecting the prices and quantities manufactured by profit-maximizing firms. We show that market prices with informational frictions reach the duopoly price with full information, at the limit. However, this convergence can take two different paths depending on the size asymmetry between countries. In particular, when countries are of very different sizes, the single market does not immediately turn into a duopoly and monopoly prices may persist for several periods. Hence, the price-reducing trade effects may take longer to appear. In view of an intense globalization process, understanding how social meetings affect market outcomes is critical for understanding the performance of international economic integration.

Using a unique large-scale clickstream data set from a mobile commerce retailer, we examine the effect of the mobile shopping app and mobile operating system versions on consumer search and purchase behaviors in mobile commerce. We find that the consumers with an up-to-date shopping app or mobile operating system (but not both) compared to previous versions conduct more searches in terms of increased product page views and time spent on product pages, which in turn results in higher consumer purchase probability. Surprisingly, the consumers with both an up-to-date shopping app and mobile operating system have reduced search activities and lower purchase probabilities. Our results show that the mobile commerce environment affects the consumer shopping process in a non-linear fashion and indicate that there exists a "sweet spot" with the right level of smoothness in the mobile shopping environment. Our computations show that when compared to the baseline of using previous versions of both, using an up-to-date mobile shopping app alone increases consumer search activities by 336 more product pages or 1,975 more seconds spent, and using an up-to-date mobile operating system alone increases consumer search activities by 976 more product pages or 7,258 more seconds spent. However, using both an up-to-date mobile shopping app and mobile operating system only increases consumer search activities by 270 more product pages or 1,569 more seconds, compared to the baseline. One more product page viewed or one more second spent increases the average consumer purchase probability by 4.38% or 1.35%, respectively.

This article proposes a multiobjective mathematical model to optimize the multiperiod aggregate production planning (APP) of multiproduct companies. Although there are many studies of lean manufacturing (LM), its integration with APP has not been studied. The present article is intended to integrate APP and LM, including an analysis of market winners, market qualifiers, and waste. The model's objective functions include the cost, lead time, and waste minimization in addition to maximizing the product quality. A solution procedure is suggested to solve the model using IBM CPLEX 12.4 software. The model is investigated in three different case studies to check its applicability and generalizability. According to the obtained results, the proposed model provides an optimized APP with regard to the major concerns of LM, including waste, overproduction, time, and sourcing. In addition, according to the sensitivity analysis, lean weighting of the objective functions provides a better output than using equal weighting.

Industry 4.0 (I4) technologies are gaining increased importance in the manufacturing industry, as they can provide several benefits such as an increase in efficiency, lower costs, higher revenues, etc. This article empirically examines the critical success factors (CSF) for implementing I4 technologies in Indian automotive manufacturing industry. In this regard, CSF and performance outcomes of I4 technologies are identified from published literature. The relationships between CSF and performance outcomes are then examined by regression analysis. The results indicate that “Data governance” is the most critical factor, as it affects all the four performance outcomes (operational, product, economic, and responsiveness). Similarly, “Legal aspects” affects three out of the four performance outcomes (operational, product, and economic performance), while “Collaboration and teamwork” affects only operational performance and responsiveness. The study provides an understanding of factors which are critical in achieving performance outcomes about I4 technologies in the automotive manufacturing industry. The findings can also help automotive manufacturing firms toward an informed decision making in terms of various strategies required to adopt I4 technologies successfully.

When an established incumbent already exists in the market, new entrants may consider special entrance strategies for entering that market. Disruptive innovation theory suggests that new entrants may start from a low-end market and then expand into mainstream markets. A recent debate on the theory has questioned its generalizability, but such controversy originates from the attempt to apply it to any business success by a new entrant. However, different innovations require the application of different theories. Therefore, this article identifies a profitable niche market for startups and small- and medium-sized companies based on consumer preferences and determines whether disruptive innovation is likely to emerge in a particular market context. Specifically, this article investigates whether the low-end market is the profitable niche market for market entrance. It uses a choice experiment and a hierarchical Bayesian normal mixture model capable of capturing preference heterogeneity at both the individual and the segment levels to predict market entry implications in an ex-ante fashion for the wearable device market in South Korea. The characteristics of the identified niche market segment and entry product design imply that startups and small and medium-sized companies should be cautious when applying disruptive innovation theory in this context.

El eslogan ha ido adquiriendo importancia en los últimos años debido a su gran capacidad persuasiva. Además, con la situación de confinamiento que se produjo derivada de la pandemia, los publicistas se enfrentaron al problema de tener que modificar sus anuncios para adaptarlos al contexto, a pesar de contar con tan pocos recursos. El objetivo de esta investigación es ver cuáles son las características del eslogan desde el punto de vista de la Lingüística textual durante este periodo. Para ello, se seleccionaron 52 anuncios que aparecían en la cuenta de YouTube El Publicista. En total, se analizaron 77 eslóganes y se les aplicaron las siguientes variables: idioma, anunciante, sector, elemento de influencia del confinamiento, existencia de eslogan doble, tipo de eslogan doble, número total de palabras, densidad semántica, presencia de marca, modo de la presencia de marca, orientación (producto, consumidor, marca) y figuras retóricas. Para la realización de esta ficha, se han tomado los estudios de Garrido (2000), Garrido y Ramos (2006) y de Garrido, Rey y Ramos (2012). Como resultados, se observa que no existen mayores cambios en los eslóganes analizados con respecto a las investigaciones previas. Igualmente, se observa una gran presencia de la temática referente al confinamiento (54 eslóganes). Se propone seguir realizando estudios de los eslóganes y analizar la influencia de los mismos en redes sociales, así como las nuevas utilizaciones de los hashtags que están usando las compañías para difundir sus campañas

PT. XYZ is a manufacturing company that produces nata de coco pieces. Consumers of the product nata de coco pieces of food businesses such as food PT.Garuda Sidoarjo, PT. Holy Sinar Mas, PT. Borobudur Semarang and others. PT. XYZ has two types of contract supplier and the supplier is not a contract. Currently, the company in the selection of suppliers do not contract into supplier contracts sometimes have trouble. Terebut difficulties occurred because of the detailed criteria that can be used for the selection of suppliers. So in this study will berusahaan find criteria that influence supplier selection. The data in this study using the method Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). In addition, models that have been made will be implemented into a Decision Support System (DSS). The criteria that can mempengeruhi supplier selection is the sum total, the number of total quality one, a total of two quality, the total number of nata broken, the number of deliveries the maximum, the maximum number of quality one, the maximum number of two qualities, the maximum amount is broken, the number of deliveries at a minimum, the number of minimum quality one, the minimum number two quality, the minimum amount is broken, regularity, quality price and the price of the quality of the two. In addition, based on test results Decision Support System (DSS), which has made the conclusion that the system that has been created can be used later by PT. XYZ.

Servitization is the activity of selling the services provided by the product rather than the product itself. It is a business model that might be environmentally superior to conventional selling. Servitization promises accessibility to the product’s functionality, pooling of consumer use, and potentially products of better design. However, it can also inflate consumption and result in a bigger environmental impact overall. In this paper, we compare servitization with traditional selling for a monopolist durable goods manufacturer from both an economic and environmental perspective. In this comparison, we define the durability of a product as the use capacity; that is, how many usages it can endure before reaching end of life. We study the firm’s durability decision, followed by the price/fee decision, and the consequent usage in the market under each model. We find that servitization produces durability levels that are robust to customer heterogeneity, and higher than selling. Overall, environmental superiority of servitization hinges on product related costs, customer heterogeneity, and market composition. It is, however, robust to varying environmental factors in the use and manufacturing phases. When we compare environmental preferability with the economic incentives of the firm, we observe that they are not always aligned.

Product returns cost retailers billions of dollars annually. We analyze return policies (RPs) with cash refunds in the presence of wardrobers. We then analyze RPs with store credit or gift cards (SC/GC) refunds. We also analyze two-option RPs in which consumers choose between cash and SC/GC refunds. We find that for cash-only RPs, the retailer uses price to attract consumers while using the refund fraction to discourage wardrobers. SC/GC can be a good alternative to cash when consumers have high valuation for SC/GC and some SC/GC are not redeemed. With high redemption rate, SC/GC can be a good alternative when consumers make hedonic purchases and the retailer has a reasonable profit margin. We also find that single-option RPs dominate two-option RPs when genuine consumers and wardrobers have the same valuation for SC/GC, and two-option RPs can dominate when the two consumer segments have heterogeneous valuation for SC/GC. When two-option RPs dominate, the retailer gives lenient SC/GC option to genuine consumers who have a high valuation for SC/GC, and uses the cash option to decrease the cost or increase the profit from wardrobers who have a low valuation for SC/GC for some ranges of problem parameters. Moreover, when consumers have continuous valuation for SC/GC, two-option RPs dominate single-option RPs in genuine-only consumer markets. With two-option RPs, the retailer uses cash to increase profit from consumers with a low valuation for SC/GC and uses SC/GC to increase profit from consumers with a high valuation for SC/GC.

This paper studies an optimal investment and benefit adjustment problem for a target benefit pension plan. The pension sponsor can adjust the benefit level to guarantee the stable operation of the plan. The pension is allowed to invest in a risk-free bond and a stock. The weighted product of the benefit outgo and pension wealth is considered in the objective function, which is taken in the form of Cobb-Douglas utility. Thus the plan takes both the benefit level and terminal wealth of the pension into account and then the benefit payment are dependent on the financial situation of the plan. By applying dynamic programming approach, we establish the corresponding Hamilton-Jacobi-Bellman equation and derive the optimal investment-benefit strategy and the value function explicitly. The verification theorem is presented and proved. Furthermore, the recursive utility is considered as an extension and we find that the elasticity of intertemporal substitution has a positive effect on the optimal benefit level. Finally, numerical examples are given and demonstrate that this pension scheme is sustainable and can provide stable and consecutive incremental benefit payment for future generations.

The primary objective of the case study is to help students understand, model, and solve capacity planning problems (i) when the production yield is uncertain and (ii) if the yield of first production is low, the product can be produced a second time. The dimension of random yield emphasizes supply chain management challenges beyond the traditional newsvendor problem, which has a nice closed-form solution. The dimension of operational flexibility underscores the importance of modeling skills, such as influence diagrams, that can be used to brainstorm, model, and solve new problems. Extensive use of the case in graduate supply chain management courses shows that in the absence of a mathematical model, students systematically deviate from optimal capacity usage. Usually, the presence of backup flexibility reduces first-period production. However, students’ responses often suggest cutting first production too much. When it is available, students consistently overuse the flexibility of second-period production. Overall, students believed the case was challenging and that it provides a valuable learning experience.

I estimate the causal effect of increasing displayed product ratings by a half star on Wayfair.com to be a five percent increase in demand for products. This increase is driven by an increase in sales, not a change in price. Products with more ratings or that are sold by lesser known brands see a large effect of star ratings on orders, while products with fewer ratings or that are sold by well known brands see no effect of ratings on orders. Furthermore, I find the causal effect of ratings to be heterogeneous across products with different ratings — with the highest rated products seeing the largest benefit to having a marginally higher rating — but not across customers with varying degrees of experience purchasing products from the site. This heterogeneity in demand effects shows that the benefits of higher ratings are not equivalent across old and new products and sellers, indicating potential policy responses by e-commerce sites.

Five lab studies and a field study explore how power distance belief (PDB) influences consumers' preference for mass-market versus niche brands, the underlying mechanisms, and boundary conditions. We find that high (vs. low) PDB consumers are more likely to prefer mass-market over niche brands because they tend to be risk averse, which in turn increases preference for widely used brands. Consequently, the relationship between PDB and brand preferences is mediated by risk aversion. Further, when product usage contexts are risky, low (but not high) PDB consumers' preference for mass-market brands increases, whereas offering an extended money-back guarantee increases high (but not low) PDB consumers' preference for niche brands.In addition, we find that when choosing service providers (versus choosing physical goods), low (but not high) PDB consumers are significantly more likely to prefer mass-market brands over niche brands. We conclude with the implications of these findingsfor marketers, such as for their segmentation and targeting endeavors. We also provide specific tools that marketers could use, both inside and outside the store, to influence consumers' preference for mass-market versus niche brands.

In the digital age, firms continuously look for leading technologies and make products of superior quality to satisfy new and sophisticated consumers’ needs. Although this approach strives to sell a product more appealing to customers, it also renders the product more complex and difficult to use, generating the feature fatigue effect. This is characterized by feelings frustration experienced by consumers when purchasing high-tech products with many appealing features, most of which turn out to be undesired, useless, and difficult to use. We study the impact of the feature fatigue effect on a manufacturing firm’s policies in designing its product–service portfolio. We consider two periods in order to capture the effect of customers’ word-of-mouth originating from feature fatigue, which is shared with other potential customers. Therefore, we assess not only the impact of feature fatigue but also the extent to which this effect can be alleviated by after-sales service. We capture feature fatigue by first considering a base model without this effect and then comparing the manufacturer’s decisions regarding quality, pricing, and service when it has either clear or noisy effect. Our findings reveal that feature fatigue drives manufacturers to under invest in quality and to replace penetration pricing policies with skimming policies. In addition, we demonstrate that after-sales service cannot fully mitigate the detrimental effect of feature fatigue on a manufacturer’s profits.

This study examines the bullwhip effect in a manufacturing/remanufacturing supply chain consisting of one retailer, one manufacturer, one supplier, and one third-party collector. Products returned from the end users are converted to ‘as-good-as-new’ products through remanufacturing. Both manufactured and remanufactured products are used to meet the stochastic demand of the retailer. We incorporate the price of the product in the demand through an autoregressive moving average (ARMA) pricing process, realizing a market demand that evolves according to a non-standard ARMA(1,1) process. For this demand model, we employ the order-up-to inventory policy with a minimum mean square error forecasting scheme and measure the bullwhip effect at each echelon of the supply chain. We investigate the behaviour of the bullwhip effect analytically, and a numerical evaluation shows that the bullwhip effect or the anti-bullwhip effect may occur at each echelon depending on the values of the autoregressive and moving average parameters of the underlying demand process. We also investigate the effects of the remanufacturing yield, the variance of the market shock on price, and the lead times on the bullwhip effect.

A sizable research stream in marketing finds that a strong fit between a brand extension product and its parent brand encourages positive consumer responses. Yet this large body of literature fails to provide managers with specific practical guidance about how to create brand-extension fit for optimal results. The problem is a lack of understanding of what brand-extension fit really is, and there has been little work to address this issue by synthesizing the key dimensions of brand-extension fit. The current article addresses this gap by identifying the key constituent dimensions of brand-extension fit. This is an important topic because brand extensions are essential for business renewal and growth. We identify six dimensions of brand-extension fit: feature-based, function-based, resource-based, usage-occasion-based, market-based, and image-based fit. Each dimension addresses a different aspect of brand-extension fit and suggests ways for brand managers to create brand-extension fit. Less expected is that studies that use a strict subset of these dimensions overweight those fit dimensions that are included, and the associated estimated coefficients are biased. From a managerial perspective, counterfactual analysis also shows that reliance on a strict subset of these dimensions results in suboptimal decisions.

Within the context of a theoretical model where an increase in the proportion of foreign-invested firms is interpreted as increase in foreign direct investment (FDI), this paper shows that, through its impact on firm capability and revenue, FDI can affect the quality of goods produced by domestic firms in host economies. We show that, in the presence of positive productivity spillovers, an increase in the proportion of foreign-invested firms lowers the cut-off capability of domestic firms, which allows some relatively inefficient domestic firms to enter the industry thereby contributing to a decrease in product quality. An increase in the proportion of foreign-invested firms affects firm revenue through two channels. On the one hand, an increase in the proportion of foreign-invested firms enhances productivity, which contributes to an increase in firm revenue. On the other hand, entry of new domestic firms also increases the level of competition within the industry, which puts a downward pressure on firm revenue. We conclude that, in the presence of positive productivity spillovers, an increase in FDI decreases the quality of goods produced by domestic firms in host economies only if its impact on firm revenue is sufficiently small (or negative). Using data from China’s beverage manufacturing industry, employing the nonlinear seemingly unrelated regression technique on firm level data and without explicitly measuring quality, we estimate the impact of an increase in the proportion of foreign-invested firms on the product quality of domestic firms. Our empirical analysis suggests that a 1% increase in the proportion of foreign-invested firms decreases the product quality of domestic firms by more than 0.6259%.

A challenge for online retail firms is managing stockouts when substitute products are available. Firms have options to set prices or offer substitute products to retain or release the consumers following stockouts. We develop a game-theoretic model in which competing online firms face the decision whether to price low enough so that, following product stockouts, their consumers remain in their stores by turning to unfamiliar substitute products that are in stock or even to attract their competitor’s consumers following stockouts at their competitor, or price high enough to release the consumers to the competitor. We demonstrate that our model’s unique equilibrium is one of three types: retain-consumer, release-consumer, or all-firm-i-consumer. Our analyses of the equilibria show that firms have the opportunity to use prices as a stockout recovery mechanisms, but surprisingly, they may choose not to do so under certain circumstances, dependent on the consumer search costs of unfamiliar substitute products on their sites.

Firms offer a variety of products to meet different customer needs. In many horizontally differentiated markets, prices are stable, and firms make infrequent adjustments to their product lines. Although prior research focused on product line design, we investigate how firms should allocate their marketing effort when their product lines are fixed. We propose a simple model to analyze product line marketing. Our model exhibits a flagship product effect in which the firm’s optimal marketing effort is concentrated, provided that the ratio between consumer tastes dispersion and the convexity of the cost of marketing effort is below a threshold. The flagship product is selected according to a marketing effort allocation index that measures the trade-off between a product’s markup and its potential market share. This result is robust with or without competition and whether prices are exogenous or endogenous. Firms often experience shocks to their marketing cost because of technological improvement or externalities. If a monopolist’s cost of marketing effort declines, she should place more emphasis on a low-utility, high-markup product. Conversely, if the cost increases, the monopolist may find it beneficial to focus her marketing effort on a high-utility, low-markup product. When multiproduct firms compete against each other, we show that if the opponent’s cost of marketing effort decreases, there can be a spillover effect, in which the firm benefits from the opponent’s cost reduction, thereby leading to a win-win situation. This paper was accepted by Dmitri Kuksov, marketing.

Guarantee credit financing (GCF), allows banks to offer loans to capital-constrained retailer (he) based on the guarantee contracts offered by the manufacturer (she). Therefore, this study investigates the signaling role of guarantee contracts when the retailer is less informed about its product's market potential. In particular, we explore a joint contract of guarantee credit and production quantity to deliver the manufacturer's demand information. We add a framework to the capital-constrained supply chain with asymmetric demand information under GCF. Using a signaling game to capture the demand information asymmetry, we identify the strategic interaction between the retailer and the manufacturer under GCF. Also, we investigate the value of GCF when both GCF and trade credit financing (TCF) are viable. We find that the single guarantee contracts cannot signal the manufacturer's demand information when the production cost is less than a threshold, otherwise, only the separating equilibria survive the intuitive criterion. Besides, the findings reveal that the demand information asymmetry can either benefit or harm the retailer or the manufacturer, but cannot benefit both of them. In addition, GCF remains an attractive financing option when both GCF and TCF are viable. A joint contract of guarantee credit and production quantity can be used to deliver the demand information if the guarantee contracts are invalid. Our paper helps to explain the impact of asymmetric demand information on supply chain partners’ decisions under GCF and sheds light on the design and use of guarantee contracts.

Interorganizational fraud, or fraud that occurs between organizations, is a critical component of supply chain fraud and supply chain relational risk, yet empirical evidence on the scale of interorganizational fraud and its antecedents remains scant. Despite its hidden nature, interorganizational fraud can have major implications for supply chain performance. Based on the theories of transaction cost economics, agency theory, and the fraud triangle, widely used in accounting and auditing research, five potential antecedents of supply chain fraud are considered and compared with reported losses due to interorganizational fraud. The data collected via a survey questionnaire with a sample of 151 supply chain employees in manufacturing demonstrate that informants estimated median losses due to interorganizational fraud to be 9% of their firm's total revenue. The most common types of fraud reported include product quality fraud, pricing/invoicing fraud, and corruption. Using a two-step generalized method of moments technique for estimation, the results found that transactional complexity, competitive pressures facing the supply chain, and weak firm ties were significantly related to interorganizational fraud, and that supply chain monitoring and ethical sourcing were not significantly related to interorganizational fraud. These findings contribute to the research on relational risk, supply chain risk management, and opportunism.

In this paper, we investigate the problem of whether a retailer should bargain over the wholesale price of a product with a manufacturer or accept the price unilaterally determined by the manufacturer. To investigate the problem, we develop a game-theoretic model describing a supply chain organized by one manufacturer and one retailer. Intuitively, if there is a bargaining opportunity, a retailer is better off bargaining over the wholesale price rather than simply accepting the price determined by the manufacturer. Consistent with this intuition, we first show the benchmark outcome that the retailer achieves a higher profit through bargaining over the price when the manufacturer uses only a single-channel supply chain, in which the manufacturer sells only through the retailer. Conversely, however, we demonstrate that this intuitive result can be completely reversed in a dual-channel supply chain environment, in which the manufacturer is able to sell products not only through the retailer but also directly to end-consumers. Specifically, we find that if a retailer's bargaining power is sufficiently strong and if consumers' substitutability between channels is substantially high, full acceptance of the wholesale price dictated by the manufacturer earns the retailer a higher profit than bargaining. This counterintuitive result is a warning to retailers in dual-channel environments because if a retailer does not accept the wholesale price dictated by a manufacturer, but heedlessly exploits its strong power and bargains with the manufacturer, it may ultimately harm itself and reduce its own profits.

Influence maximization, which aims to find a small number of influencers in a social network to maximize the influence spread under a certain propagation model, has attracted substantial attention due to its widespread applications, such as viral marketing and social advertising. However, most of the former studies focus primarily on maximizing the influence spread of a single product, which is not very common in actual marketing campaigns. In this article, we study a novel compatible influence maximization problem for two considered products, which involves more complex product adoption decisions of users in many realistic settings. The problem is NP-hard, and the objective function no longer exhibits monotonicity and submodularity. We propose an adapted greedy algorithm to solve the problem effectively. Due to its poor computational efficiency in the seed selection, we further propose a fast greedy algorithm that integrates several effective optimization strategies without compromising the accuracy and devise an efficient heuristic algorithm to approximate the influence spread calculation. Extensive experiments over real-world social networks of different sizes demonstrate the effectiveness and efficiency of the proposed methods.

A delivery mix that includes delivery from stock and drop-shipping is of interest to many internet retailers. We consider a retailer serving a time- and price-sensitive market with two substitutable products that differ in the guaranteed delivery time and price, an express product (delivered from the stock) and a regular product (drop-shipped). In case of stockout, customers may switch from the express product to the regular product. We study how to differentiate the products in terms of delivery times and prices and how to determine the stock level to maximize the retailer's expected profit while satisfying service constraints. We solve different variants of the problem and derive insights into the optimal retailer's strategy. In addition, we study the impact of stockout-based substitution. This paper is the first to investigate time- and price-based differentiation along with inventory decisions for a retailer who relies on a hybrid distribution to satisfy a time- and price-sensitive demand subject to stockout-based substitution. When prices and stock are fixed, in addition to minimum and maximum time differentiations, a medium differentiation strategy may be optimal but depends on the stock level. When only prices are fixed, there exists a price differentiation limit below which a minimum time differentiation is optimal, and above which only the express product should be offered. For the general model, numerical experiments show that a higher stockout-based substitution leads to greater time differentiation (which is consistent with the results of previous models) and more stock. However, this would not impact the price differentiation.

Under what conditions do high levels of export concentration in a single market create vulnerability to coercive economic power? This paper examines that question through a detailed examination of the experiences of Australian export industries that lost access to the Chinese market during a recent and ongoing sanctions episode that began in May 2020. We characterize sanctions as government interventions that distort free economic exchange, and ask how markets autonomously adjust to these shocks. Despite China being a large and highly valuable export market for many affected industries, the economic – and accordingly political – impacts of sanctions have been more modest than anticipated. The reason for this lies in market adjustments. Theoretically, we extend insights from extant research on how market dynamics condition the impact of sanctions that generate ‘supply shocks’ (such as oil embargoes) to the new domain of ‘demand shocks’, modeling the process of responding to unilateral import sanctions from the perspective of export industries in a target state. We argue that losses can be diminished by three mechanisms that are understudied in the sanctions literature: trade reallocation (where buyers and sellers shift but do not lose trade partners); trade deflection (circumventing sanctions via intermediaries); and product transformation (the transformation of production processes to produce and sell entirely different products or similar products not covered by sanctions). Empirically, we describe variation in the adjustment processes undertaken in nine Australian industries affected by the loss of the Chinese market, and explore the conditions under which these adjustments are more or less viable, depending upon differences in market structures and dynamics across products.

Given the increased purchasing powers in overseas markets and the existence of purchasing agents, international brands may reconsider their entering strategies. In this paper, we use a game-theoretical approach to investigate the strategy of an international brand to carve out a niche in overseas markets with considering of purchasing agents and multinational tax rules. At the beginning, the brand serves the domestic market only, and the purchasing agent acts as a domestic consumer but resells the product to the overseas market. To enter the overseas market, the brand can choose to operate an overseas store itself or sell through a cross-border e-commerce platform, with the existence of the purchasing agents. We derive the optimal strategies for the brand and the impacts of purchasing agents. Our results show that the brand prefers to enter the overseas market once the two overseas strategies are profitable but sticks to domestic market under certain circumstances, which depends on the tax policy and consumers’ valuation discount of buying from an agent. For the optimal overseas strategies of the brand, selling through a platform is more likely to be a profitable option than managing an overseas store. When both overseas strategies are profitable, the brand’s optimal choice depends on tax rules only. Interestingly, the brand does not always have the motivation to drive the purchasing agents out of the overseas market by adjusting retail prices. The existence of purchasing agents may help achieve a win-win situation for the brand and consumers under certain conditions.

Humanitarian aid organizations generally need to decide how to allocate their limited budget among different materials for disaster preparedness and disaster response. The budget can either be used before the disaster for stocking decisions under uncertainty or it can be used after the disaster to satisfy the required demand at a higher cost when the uncertainty is resolved. In this study, we aim to decide how many of each type of material to procure before and after the disaster considering the budget limitations. For this purpose, we first develop single product models with and without budget constraints using a newsvendor approach. Then, we build a two-stage stochastic model with budget constraint for the two-product case and determine its optimal solution by first solving the second stage problem to allocate the remaining budget among the products after the disaster. Then, we solve the first stage problem using KKT conditions for the resulting constrained nonlinear optimization problem. Finally, we extend our analysis for multiple product cases and propose approximation algorithms utilizing the optimal solutions derived for the single and two-product cases. We provide managerial insights using our results through detailed numerical experiments, and also present a case study with real life data. It is observed that, contrary to expectations, higher quantities need to be purchased before the disaster when there is a limited budget, as compared to the unlimited budget case. When multiple products are considered, it is important to consider the interactions between the products, especially when the budget is moderate.

Indonesia has been known to have abundant natural resources and culture-based creative industries. The country is therefore vulnerable to the practice of fraud of origin. One of many industrial sectors susceptible to that particular crime is the wooden furniture businesses. In many cases, it is apparent that natural products and raw materials of Indonesia are being exported without listing the country as the place of origin. The most common Indonesian material falls within this illegal practice are timber products. In the province of Central Java, Jepara has been a prominent center of timber industry producing high quality timber products and wooden raw materials. From a unique standpoint, the timber industry in Jepara is deeply rooted to the culture and identity of the natives, making the attempt to separate the discussion between timber industry and the people of Jepara not only imprudent but virtually impossible. By looking at the statistic in which Jepara’s public education level is assessed to be still below the national standard, and as well bearing to the general fact that the timber actors in Jepara are more focused on product sales rather than important technical aspects such as certification of origin, it should be projected that crimes such as fraud of origin could be easily committed in Jepara. This study is using a comparative advantage theory and theories or models of H-O to investigate how the practice of fraud of origin in Jepara occurs and how to resolve such problem.

Researchers have recently begun investigating how visual elements affect brand positioning. However, little is known about the effect of brand typeface features on brand premiumness. This paper proposes and verifies that letter case affects consumers’ perceived brand premiumness. Eight experiments, including one eye-tracking experiment, reveal that consumers perceive brands that use all uppercase letters (“uppercase brands”) as more premium than those that use all lowercase letters (“lowercase brands”). We refer to this effect as the “uppercase premium effect.” This effect is induced by the perceived conspicuousness of uppercase brands, a process which in turn is moderated by the product's social visibility. The effect is reversed for consumers who prefer subtle signals (“inconspicuous consumers”) because these consumers are likely to perceive a conspicuous uppercase brand as gaudy. Whereas status-motivated consumers are more likely to choose uppercase brands due to the increased premiumness perceptions, the increment in such perceptions does not further influence the purchase decisions of consumers indifferent to expressing status. We conclude with a discussion of theoretical and practical implications and offer suggestions for further research.

Introduction Political acceptability and successful implementation of tobacco control policies at the point of sale may depend on, among other factors, tobacco retailers’ level of support for these policies. This study quantified the level of support among small tobacco retailers for four point-of-sale tobacco control policies and its association with three predictors. Methods We used cross-sectional telephone survey data (August 2019) of 508 small tobacco retailers in England. Weighted logistic regression analyses examined associations between support for the product display ban, price display ban, minimum pack size, and standardized packaging, and self-reported importance of tobacco sales for a business, contact with the tobacco industry, and the perceived impact of the policy on their overall business. Results A majority of retailers support minimum pack size (66%), product display ban (65%), price display ban (54%), and standardized packaging (55%). The importance of tobacco sales was not associated with support for the policies. More frequent contact with the tobacco industry was associated with higher odds of support for minimum pack size (OR: 2.01, 95%CI:1.25–3.21), but not with the other three policies. The negative perceived impact of the policies, compared with neutral, was associated with 1.5 to three times lower odds of support for all four policies. Conclusion In England, small retailers’ support for the four point-of-sale tobacco control policies varied between 54% and 66%. Support seems unrelated to the perceived importance of tobacco sales, and contact with the tobacco industry, but seems strongly related to the perceived impact of tobacco control policies on their business. Implications This study shows that small independent retailers’ support for point-of-sale (PoS) tobacco control policies is fairly high and that the lack of support voiced by retail trade organizations is not representative of the views of retailers in England. Support rates may be further improved by addressing retailers’ perceptions of the impact of policies on their business. Support was not related to retailers’ perceived importance of tobacco sales for their business and their contact with the tobacco industry. The industry rhetoric is not supported by our findings, as the majority of small independent retailers in England support tobacco control regulations.

Recent advances in information technology, advanced manufacturing (robotics, 3D printing, etc.), and logistics have allowed firms to customize their products to the specifications of individual consumers, who, in turn, prefer these products to standard ones. In the unlikely event that customized products do not match expectations, however, consumers often feel entitled to a return. Should firms offer returns on customized products? We examine this question via a Stackelberg game model, in which the firm (leader) decides the prices and returns policies for its customized and standard products; consumers (followers) decide which product to buy, given the initial noisy valuations and, upon experiencing the product, whether to return it. Both parties act strategically: Forward-looking consumers incorporate the real option value of possible returns into their initial purchasing decisions, and the firm incorporates consumers’ best purchase and return response into its pricing and returns policy decisions. Our model produces three key insights. First, firms can use customized products to induce some consumers who otherwise would buy and return a standard product to switch to lower-return-rate customized products. Second, it may be optimal to offer returns on customized products, despite their lower salvage value. Third, firms can increase profits and reduce (total) returns by offering returnable customized products. This paper was accepted by Duncan Simester, marketing.

Today, in the market with ever-changing consumer preferences, three-dimensional (3D) printing is becoming an overwhelming trend. In this paper, we explore the use of 3D printing in mass customization (MC) programs. We consider the case when 3D printing brings extra self-design fun to consumers, which is highlighted in MC practices of the auto company BMW and the furniture company Poltrona Frau, and also changes the cost formula (i.e., the marginal product variety cost) of the MC product. In addition, the roles played by the risk attitudes of the MC manufacturer and consumers, consumer returns, as well as consumers’ time sensitive behaviors, are also uncovered. We find that under the case with a low consumer's willingness to pay for the traditional “ready-made product variety enjoyment” (RPVE), even the maximized product variety level and the additional self-design fun cannot make the 3D printing based MC more profitable. In addition, compared to the markets with risk-averse and risk-neutral consumers, the 3D printing based MC can increase more MRBs and a higher consumer surplus by simultaneously highlighting the high self-design fun and the high RPVE in a market with risk-seeking consumers. The high flexibility and responsiveness of 3D printing also shows its advantages in remanufacturing the consumer returned MC items and enhancing MC programs’ overall lead-time. Finally, applying 3D printing in creating molds can also help the MC manufacturer tackle demand uncertainties. These findings all provide a good reference to the application of 3D printing in MC operations.

We consider a large group of consumers who decide whether or not to buy a durable good offered by a firm. Without previous experience with the product, consumers rely on the ratings of past purchasers to evaluate the product goodwill and make optimal decisions. The consumers have heterogeneous intrinsic rating behaviors and preferences. For example, the population may include avid fans who tend to purchase at early stages and over-rate the product. What are the firm’s optimal pricing and marketing strategies in the face of such heterogeneous market? To answer this question, we model the problem as a Stackelberg mean-field game, with the firm acting as leader and the consumers as followers. We determine the conditions under which a Stackelberg equilibrium exists and provide a numerical scheme to compute the optimal prices, marketing activities, aggregate rating, and market share. We provide some numerical examples to illustrate the type of insights that can be obtained with our model. For instance, we show that it is useful to compare the fairness of different rating aggregators, and can anticipate herding behavior triggered by biased raters.

We study the production/inventory competition problem between two manufacturers each adopting the co-production system to process a raw material into two products in fixed proportions that are substitutable between the manufacturers. We first consider the one-period problem where the demands for the two manufacturers’ products are uncertain and independent. The unmet demand of one manufacturer's product can be met by the other manufacturer's leftover stock of the same product, if available, and is lost otherwise. The manufacturers compete for the substitute demands by choosing their own purchase/processing quantities. We show the existence of the unique Nash equilibrium processing quantity, and examine the impact of competition by comparing the total equilibrium quantity of the game with that of the centralized-decision case. We then study the multi-period production/inventory competition problem in which the manufacturers make decisions in each period according to the initial inventory levels of the products and the rivals’ decisions. We show the existence and uniqueness of the Nash equilibrium strategy and that the equilibrium strategy has the simple base-stock structure. We then consider the case where the manufacturers’ demands are correlated. In addition, studying the case where the manufacturers are capacitated, we show that the unique Nash equilibrium exists and has a modified base-stock structure. We further generalize the results to the infinite-period case and the case with more than two products. Finally, numerical studies are conducted to investigate the impacts of the model parameters on the equilibrium outcomes and get some managerial insights from the analytical findings.