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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.

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.

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.

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.

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.

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.

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.

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.

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.

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%.

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.

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.

Customer loyalty programs are often used by retailers as an important marketing tool. As an essential element of loyalty programs (LPs), the reward amount invested by the retailer is often linked to retailer's profit and customer behavior. We consider a retailer who sells a type of product in two periods to strategic customers. The retailer makes inventory ordering and loyalty program investment decisions. Customers decide whether to purchase immediately (in period 1) to receive the product and reward, or to wait for a markdown discount but face the risk of stockout. We have focused on three main questions: (1) How does the loyalty reward investment decision impact strategic customers’ behavior? (2) What are the optimal decisions and profits for the retailer when investing in a loyalty program? (3) What are the factors influencing the reward investment decision? We find that investing in the loyalty program induces more customers to make an early purchase, leading to a higher inventory ordering decision and more profit for the retailer. The benefits from reward investments are significantly affected by the product's cost and customers’ valuation of the product. Our results shed light on the reward investment decision of LPs. For products with high profit margins and market-determined prices (valuation approximates price), the retailer should invest in a loyalty program to achieve better profits.

In the implementation of activities we often find what is called a project. The project is an activity that must be completed in accordance with the specified target and time, so that the project can be regarded as a success in project implementation. One of the projects in question is the construction project. Construction projects in their implementation we often encounter various kinds of problems that arise from the ele-ments involved in them, so this can hamper the success of a project that is being implemented. One problem that arises from the contractor factor and contract specification. The purpose of this study is to find out one of the main inhibiting factors in the successful implementation of construction projects in Aceh Province. Classification of construction services for respondents is all construction services from the mid-dle class (M) to large classes (B). The data obtained the total population of construction services as many as 508 contactors from observa-tions of projects that have been completed from 2010-2015 with funds from the Aceh Budget (APBA). By using the Slovin formula a total sample of 84 contractors was found. The method used in this study is a combined method, namely qualitative and quantitative methods through questionnaires. The independent variables reviewed are the contractor factor and the contract specification factor while the depend-ent variable is the success of the project. For statistical analysis the data process is done by using validity and reliability tests, while analyz-ing the data is done by using multiple linear regression with the help of Product Solution and Service Statistics (SPSS) version 22. The results of the study indicate that the contractor factor is one of the main inhibiting factors in the successful implementation of the project in Aceh Province., {"references":["Ervianto, WI 2004, Teori Aplikasi Manajemen Proyek Konstruksi, Salemba Empat, Yogyakarta","Syah, M 2004, Kiat Manajer yang Sukses, Binapura Aksara, Jakarta.","Dipohusodo, 1995, Manajemen Proyek & Konstruksi Jilid 2, Kanasius, Yogyakarta","Ock, JH dan Han, SH 2003, Lesson Learned form Rigid Conflict Resolution in an Organization: Construction Conflict Case Study, Journal of Management in Engineering, April 2003.","Susila, H., 2012, Faktor-faktor Penyebab Konflik dalam Pelaksanaan Proyek Konstruksi, Jurnal Teknik Sipil dan Arsitektur, Universitas Tunas Pembangunan Surakarta, Volume 11. No. 15, Maret 2012, ISSN: 2301-668X.","Aderiani, R., Tantyonimpuno, S., dan Adi, W, J, T., 2005, Identifikasi Konflik yang Terjadi pada Pelaksanaan Proyek Konstruksi Gedung, Prosiding Seminar Nasional Manajemen Teknologi I, Program Studi Magister Manejemen Teknologi Institut Teknologi Sepuluh Nopember, ISBN: 979-99302-0-0.","Priyatno, D 2010, Teknik Mudah dan Cepat Melakukan Analisis Data Penelitian dengan SPSS dan Tanya Jawab Ujian Pendadaran, Gaya Media, Yogyakarta.","Ferdinand, A., 2006, Metode Penelitian Manajemen, Universitas Diponegoro, Semarang."]}

The existence of varied form of corporation contract in Indonesia cannot be separated from the existence of corporation forms regulated in the constitution. The forms of corporation as like companies, firms, commanditer companies, PT, and cooperation which come from the constitution of colonial Netherland are surely influenced by the capitalist of western economic system. Meanwhile, in Islamic law there are mechanism of corporations in every sector, like al-Shirkah, al-Mudharabah, al-Muzaro’ah, and al-Musaqoh. This research discusses various mechanisms of corporation that are regulated in the constitution in Indonesia and in Islamic law, and the comparison between both of them. By using qualitative research design through library research in each law product, analyzing the content and comparative analysis, it can be concluded that the various forms of corporation in Indonesia can be made same with (al-Qiyas al-Musawi) the various forms of corporation in Islamic law. This similarity can be seen from the agreement, the goal, the right, the true effort, the important of the agreement, the authority of the people, and the separation aspect. However, there is exception in the law of obligation. The obligation law in the mechanism of the corporation contract cannot be true (haram) since it is not in line with al-Qur’an and the rules in the various forms of corporation contract in Islamic law. Keywords : corporation contract, positive law, Islamic law, al-Qiyas al-Musawi

Banking development in Indonesia is really influenced by the condition of economic macro. The dynamic fundamental change of economic macro makes banking world apply a strategy to stand and develop. Even though the Syari’ah banking practice in Indonesia that applies profit sharing system is expected independent from the fundamental of economic macro, the decision made cannot be separated from the fundamental of economic macro. The decrease of Rupiah exchange value, the decrease of BI rate, and the increase of fuel price are expected becoming positive signal for Syari’ah banking in Indonesia. This research aims at explaining the relation between the fundamental variables of economic macro and Syari’ah banking works. This research employed an explanatory research design. The population is all Syari’ah banks that expose the monetary report in 2009-2014. There are 11 Syari’ah public banks, 24 Syari’ah companies, and 31 Syari’ah office channelings. The findings reveals that (1) the decision of BI to increase BI rate will be applied if the number of money in society are too much; in the contrary, if the number of money in society are too little, BI will decrease BI rate. From analyzing the data, it shows that BI rate influences positively to Syari’ah banking works. (2) Inflation influences positively to Syari’ah banking works; it means that if inflation increases, Syari’ah banking works becomes better. If the communities ability to buy decrease, the demand of money increase more. This makes syariah banks do no have idle money. (3) the contribution of money exchange variable, BI rate, and inflation influence the Syari’ah banking works. The contribution of X1, X2, and X3 to Y can be seen from R2 (68,7 %), and 31,3 % is influeced by the exchange money variable, PDB, product variation, profit sharing, and promotion. Keywords ; Rupiah exchange value, BI rate, Syari’ah banking work

Traceability enables manufacturers to link the work performed by individual workers with downstream effects in a supply chain. With good traceability, firms may be able to observe the downstream quality of specific product units, recognize lapses in product reliability, connect those lapses to workforce dynamics occurring upstream in the supply chain, and correct the problems by improving those dynamics. To study this potential, we focus on the impact of worker turnover on product reliability. We collect and integrate (1) data reporting factory worker staffing and turnover within a major consumer electronics producer's supply chain and (2) traceable data covering the component quality and field failures—i.e., replacements and repairs—of nearly 50M consumer mobile devices over four years of customer usage. Devices are individually traced back to the factory conditions and staffing, down to the assembly line-week, under which they were produced. Despite the manufacturer's extensive quality-control efforts, each percentage-point increase in the weekly rate of workers quitting from an assembly line (its weekly worker turnover) is found to increase field failures by 0.74-0.79%. In the high-turnover weeks following paydays, eventual field failures are strikingly 10.2% more common than for devices produced during the lowest-turnover weeks immediately before paydays. In other weeks, the assembly lines experiencing higher turnover produce an estimated 2-3% more field failures on average. The associated costs amount to hundreds of millions USD. We demonstrate that staffing and retaining a stable factory workforce critically underlies product reliability and showcase the value of work traceability in supply chain operations.

The top online marketplaces in the world, such as Alibaba, Amazon, eBay and others, sold $2.7 trillion in 2020, or 62% of global web sales that year. Despite the promise of unfettered access to customers, the reality is that most sellers struggle with unprecedented unauthorized “rogue resellers.” These often anonymous, third party individuals and firms may not provide the quality experiences aligned with customers’ expectations of a brand and often market their goods in competition with trusted partners. This requires a systematic battle plan in order to effectively protect the seller’s brand equity, service promise and authorized distribution network. We describe the channel war that is at work and the forces fueling its development. We explain how rogue reseller activities drive down pricing, increase channel competition and conflict, impact customer experience, and harm brand equity. We recommend revising product policies, procedures and agreements to begin to differentiate products from those sold by unauthorized parties. We also recommend a legal strategy to complement these efforts. Critical steps include regular and active enforcement, as well as implementing services, benefits and quality controls for the brand’s products that cannot be replicated by unauthorized sellers and requiring authorized distributors and retailers to maintain those benefits and controls.

Credit purchasing has seen dramatic growth recently, requiring retailers to adapt their operations in response to an online platform's strategic credit offering. This article presents a model for exploring the platform's strategy for offering credit and the retailer's response, considering consumer spillover, that is, how much the benefit of credit outweighs the drawbacks. The consumers differ in their disposable personal incomes and valuations for the product, and they may perceive a spillover from the credit. We study an integrated system, where the platform acts as a retailer and determines the credit-offering strategy and the price simultaneously. We find that the platform will offer credit only when the spillover is above a given negative threshold, and will charge an interest rate for credit only when the spillover is positive. In addition, the price exhibits a nonmonotonic change with the credit spillover, but the demand remains unchanged at a high level. We then extend the analysis to an independent system, where the retailer sells through the platform. We find that the revenue-sharing percentage the retailer pays is critical for the platform to optimize its credit strategy. Specifically, the platform will never offer interest-free credit when the percentage is low, but in other cases may do so and the credit offering does not harm the retailer's profit. Interestingly, when the spillover is moderate, the demand may decrease instead of increase, indicating a deviation from the presumed intention of offering credit.

This paper develops a model for a cold chain operated among a single product manufacturer and multiple retailers to minimize the total cost of the chain. A distinguishing feature of the cold chain is that the quality of the product degrades with time. The storage temperature and time influence the degradation rate. In this context, quality can be measured using multiple distinct indices. A global stability index is used to quantify the overall quality. The non-Arrhenius model is exclusively applied to measure the quality degradation during the transportation and at a retailer's storage as the product moves in the cold chain. Optimal replenishment times for the manufacturer and retailers are decision variables and the cold chain's total cost includes the cooling cost, carbon emission cost, and loss of value in addition to the traditional supply chain costs. It is found that for a given manufacturer's replenishment time, the total cost is convex on each retailer's replenishment time. Hence, an algorithm is developed based on this property to find the optimal replenishment times for the manufacturer and retailers. This paper also investigates how specific cold chain parameters influence optimal decisions and the total cost. The analyses show that the resulting costs will be significantly higher if quality degradation is ignored in a cold chain.

Combination products with a wide range of clinical applications represent a unique class of medical products that are composed of more than a singular medical device or drug/biological product. The product research and development, clinical translation as well as regulatory evaluation of combination products are complex and challenging. This review firstly introduced the origin, definition and designation of combination products. Key areas of systematic regulatory review on the safety and efficacy of device-led/supervised combination products were then presented. Preclinical and clinical evaluation of combination products was discussed. Lastly, the research prospect of regulatory science for combination products was described. New tools of computational modeling and simulation, novel technologies such as artificial intelligence, needs of developing new standards, evidence-based research methods, new approaches including the designation of innovative or breakthrough medical products have been developed and could be used to assess the safety, efficacy, quality and performance of combination products. Taken together, the fast development of combination products with great potentials in healthcare provides new opportunities for the advancement of regulatory review as well as regulatory science., Graphical abstract Image 1, Highlights • Full overview of the origin, definition and designation of combination products. • Regulatory review and evaluation of the safety and efficacy of combination products. • Regulatory science and its future perspectives of combination products.

Platform-hardware business models (e.g., integrating a software technology platform into a hardware device such as a smartphone) have been widely applied in various industries. This study investigates the response of competing original equipment manufacturers (OEMs) when the developer strategically updates the platform quality. Consumers have two-dimensional valuations of the product: one valuation for the device provided by the OEM and another valuation for the platform provided by the developer. The developer offers two types of agreements: acceptance and rejection of preinstallation of core services that profit the developer. OEMs can preinstall the core services and pay nothing to use the platform, or they can pay a wholesale price for the platform and reject the installation of the core services. We propose a game-theoretic model to examine the strategic agreement choices of dominant and weak OEMs when the developer strategically offers an updated platform quality to enhance a weak OEM's competitiveness. We find that the developer benefits from the OEMs’ acceptance only when the exogenous wholesale price for the dominant OEM is low and the cost difference is moderate. Also, when the research and development (R&D) efficiency is high, an increase in the cost difference induces a conversion from acceptance to rejection for the dominant OEM, and an opposite outcome for the weak OEM. One OEM's installation acceptance may enhance or weaken the advantage of the other OEM's acceptance for the consumer surplus, depending on the value of the R&D efficiency. Several extensions are examined to complement the basic model, and implications behind each strategic choice are revealed.

Improved supply chain optimization strategies can play a major role in addressing global food security and safety in years to come. In particular, tighter safety regulations, changing consumer quality requirements and more stringent market competition call upon integrated supply chain decision-making frameworks that explicitly consider product quality control. This effort requires metrics of quality that accurately reflect product physico-chemical properties, as well as consumer purchasing preferences. However, a critical challenge linked to embedding the complex dynamics of the evolution of product quality in time within supply chain models is the large-scale nature of the ensuing optimization problems, which are computationally intractable even for moderate-size, single-item systems. In the present work, we introduce a computationally efficient optimal production and distribution planning framework for perishable products having multiple quality attributes that evolve in time as a function of environmental conditions during shipment and storage. We also propose a model reduction strategy and a decomposition framework that enhance the scalability of our approach. We perform extensive numerical simulations using different network instances to validate our theoretical findings, as well as to demonstrate the advantages of the proposed supply chain management scheme.

There is a lack of affordable and acceptable sanitation solutions for dense, low-income urban settlements. One option that has been proposed is container-based sanitation, where a sealed cartridge installed in a free-standing toilet is regularly changed and adequately separates users from their excreta. Though container-based toilets are considered a safely managed sanitation solution that meets the Sustainable Development Goal for sanitation, little is known about user experiences to inform how such a solution should be viewed by governments. We conducted a longitudinal prospective cohort study of changes in objective and subjective measures of sanitation quality due to the Clean Team Ghana (CTG) container- based toilet service in Kumasi, Ghana from June to December 2019. We collected data immediately prior to installation of a toilet and 10 weeks afterwards for 292 customers. Most initially used public toilets with good structural quality, but sometimes had poor cleanliness, a lack of handwashing facilities, and required a 14.3 minute mean round trip time to use. The evaluation found that CTG delivers a high-quality service that positively impacts the quality of life of CTG customers, as well as saving them money, reducing gender gaps in quality of life, and addressing the needs of those with physical disabilities. Satisfaction with CTG toilet and service characteristics was high, with the largest increases for satisfaction with smell, comfort, disgust, and privacy. Women in particular were positively impacted both for explicitly gendered indicators like the ability to practice menstrual hygiene management, and other indicators where women scored lower than men at baseline, including ease of access, ease of use, and cleanliness. Use of the service also benefitted those who had been unable to use a toilet for physical or social reasons beforehand. Problems with the CTG service, such as leaking, filling, smelling, or not being replaced as scheduled, were reported by fewer than 10% of customers. While one product or service does not fit the needs of all customers, this evaluation supports the growing body of evidence that container-based sanitation provides a service valued by users and acceptable to policymakers in dense urban settlements.

With the construction of smart cities and the continuous improvement of people's living standards, residents’ demand for fresh agricultural products (FAPs) has increased dramatically. Therefore, reasonable arrangement for intelligent distribution of FAP in smart cities can effectively guarantee product quality, improve distribution efficiency, reduce distribution cost, and increase customer satisfaction. In actual distribution in smart city, road conditions are one of the important factors that affect the distribution. Therefore, according to the influence of road conditions on refrigerated vehicle's (RV's) speed, the RV's speed characteristic models are established. Meanwhile, according to the characteristics of FAP, the penalty cost function based on the time window is constructed. According to the idea of fuzzy logic, the customer satisfaction evaluation model is established. Then, in order to minimize the distribution costs and maximize customer satisfaction as the optimization goal of intelligent distribution in smart city, the mathematical model is built. For solving this model, an improved quantum-behaved particle swarm optimization algorithm (IQPSO) is proposed. Finally, the effectiveness of IQPSO is verified by simulation. The results show that IQPSO also achieves good results, and the model constructed can effectively balance the relationship between the distribution costs and customer satisfaction when distributing FAP in smart city.

We consider a fast-fashion brand that cooperates with a luxury brand, jointly launching a co-branded product. The impacts of the co-branding on the two brands’ original product lines are uncertain, and each brand can be either risk averse or risk neutral. Consumers, driven by exclusivity or conformity, are classified as either snobs or conformists. The equilibrium retail price, quality investment, and investment support are derived. The optimal market-targeting strategy for the fast-fashion brand as marketer of the co-branded product, is identified. We show that the fast-fashion brand is willing to give up either the conformist or the snob market under certain conditions, even when it has sales in both markets. In addition, given a particular market-targeting strategy, the fast-fashion brand benefits from its own risk aversion if the cost of risk is low, but the luxury brand is always worse off; the luxury brand may benefit from the fast-fashion brand’s risk aversion, however, if the market-targeting strategy is changed. Both brands are worse off when the luxury brand is risk averse.

The demand decreases as the price increases. Also, the demand rate for fresh goods depends on its freshness, which can be assessed by its sell-by date. Furthermore, a large pile of consumer goods displayed in a supermarket often provokes consumers to buy more due to its freshness, variety, or visibility. With larger business transactions, the supplier usually requests a good-faith deposit (or an advance payment) to discourage the order cancelation. On the other hand, the retailer likes to hold some portion of the purchase amount until the business transaction is completed and satisfactory (or a credit payment). Consequently, an advance-cash-credit (ACC) payment scheme, which is a combination of advance, cash, and credit payments, becomes commonly used in business transactions. In this study, we explore an inventory system in which: demand curve depends on unit price, displayed volume, and sell-by date; and the supplier and the retailer agree with an ACC payment scheme. The objective for grocery stores is to maximize the total profit by finding its price and order cycle simultaneously. We derive theoretical results, and then propose an algorithm. Finally, we perform sensitivity analyses to gain the following managerial insights: (i) An increase in stock efficiency significantly reduces selling price and cycle time while tremendously raising total profit. (ii) Credit payment generates the lowest selling price but the highest profit among all payment types. (iii) An increase in shelf life through preservation technology investment significantly raises total profit while slightly increasing the unit price and cycle time.

Packaging is the first thing seen in a product and today many companies are focused on developing product packaging designs to compete in the market. The improvements in the type and design of packaging can be done PRIMKOPTI SWAKERTA Semanan to maintain customer loyalty. The purpose of this dedication is to provide knowledge of more environmentally friendly packaging alternatives to support the sustainable development of the tempeh industry and its processing in Semanan. Devotional activities begin with an introductory survey and then continue with training conducted online with the devotional team and tempeh craftsmen. The delivery of several training materials was done in parallel related to quality improvement, some of these materials such as the application of Good Manufacturing Practice, maintenance of production machines and food packaging. The survey results showed that 66.7 % of craftsmen use clear plastic with a simple design and some do not even use labels. The remaining 33.3 % of tempeh craftsmen use a combination of aluminium foil and plastic packaging. Alternative solutions are provided in improving the quality of tempeh products through banana leaf packaging. Banana leaves help the process of fermentation on tempeh and also increase consumer interest in buying because it is preferred. Kraft paper packaging is recommended for use because it can reduce the risk of rancidity on tempeh chips and extend the shelf life. Semanan tempeh makers can use this food packaging alternative to attract back consumers' interest that decreased during the pandemic.

As global supply chains become more developed and complicated, supplier quality has become increasingly influential on the competitiveness of businesses during the Covid-19 pandemic. Consequently, supplier selection is an increasingly important process for any business around the globe. Choosing a supplier is a complex decision that can result in lower procurement costs and increased profits without increasing the cost or lowering the quality of the product. However, these decision-making problems can be complicated in cases with multiple potential suppliers. Vietnam's textile and garment industry, for example, has made rapid progress in recent years but is still facing great difficulties as the supply of raw materials and machinery depends heavily on foreign countries. Therefore, it is extremely important for textile and garment manufacturing companies in Vietnam to implement an effective supplier evaluation and selection process. While multicriteria decision-making models are frequently employed to assist with supplier evaluation and selection problems, few of these models consider the problem under the condition of a fuzzy decision-making environment. The aim of this paper is to create a hybrid MCDM model using the Fuzzy Analytical Hierarchy Process (FAHP) model and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to assist the supplier selection process in the garment industry in a fuzzy decision-making environment. In this study, the FAHP method is used to evaluate the performance and the weight of each criterion. TOPSIS is then used to rank all potential suppliers. The proposed model is then applied to a real-world case study to demonstrate both the process of calculation as well as its real-world applicability. The results from the case study provide empirical evidence that the model is feasible. The proposed approach can also be used in combination with other MCDM models to better support decision makers and can be modified to be applied in similar supplier selection processes for different industries.

Background The rise of investigative and commercially available cell therapy products adds a new dynamic to academic medical centers; that is, the management of patient-specific cell products. The scope of cell therapy has rapidly expanded beyond in-house collection and infusion of cell products such as bone marrow and peripheral blood transplant. The complexities and volumes of cell therapies are likely to continue to become more demanding. As patient-specific “living drugs,” cell therapy products typically require material collection, product provenance, transportation and maintenance of critical quality attributes, including temperature and expiration dates. These requirements are complicated by variations in product-specific attributes, reporting requirements and interactions with industry not required of typical pharmaceuticals. Methods To manage these requirements, the authors set out to establish a framework within the Immune, Progenitor and Cell Therapeutics Lab, the Current Good Manufacturing Practice facility responsible for cell manufacturing at Mayo Clinic Rochester housed within the Division of Transfusion Medicine. The authors created a work unit (biopharmaceutical unit) dedicated to addressing the specialized procedures required to properly handle these living drugs from collection to delivery and housing the necessary processes to more easily integrate externally manufactured cell therapies into clinical practice. Results The result is a clear set of expectations defined for each step of the process, with logical documentation of critical steps that are concise and easy to follow. Conclusions The authors believe this system is scalable for addressing the promised growth of cell therapy products well into the future. Here the authors describe this system and provide a framework that could be used by other centers to manage these important new therapies.

Protected geographical indications (PGIs) are an increasingly popular strategy for securing price premiums on food products in the interest of preserving associated rural livelihoods, however they often fail to show clear benefits for small or otherwise marginalized farmers. Their environmental record for supporting low-impact farming practices is also mixed. This case study of the PGI for Spanish almond-based desserts Turron de Jijona and Turron de Alicante details a yet unstudied form of such failures, where manufacturers seeking to scale production removed the requirement to source their primary ingredient (almonds) from the region's low-input farms and opted for intensively produced ingredients imported from abroad. This uprooting of turron from its agroecological origins highlights how the GI designation creates tension between the need to legitimate a product as rooted in traditional agrarian lifeways and the incentive to expand exports by industrial means. While previous studies show how such tension can result in agricultural intensification benefitting larger landholders within a given region, I argue this inequity and ecological risk operates at a global scale. Importantly, the turron case reveals that “quality” of a product is a moving target shaped not only by culinary legacies but also forged by a global political economy of agriculture suffering chronic overproduction. Finally, the role of the state in structuring PGI institutions more inclusively and adjudicating conflicts among actors along the value chain is fundamental to the capacity of these programs to achieve social and environmental goals.

Nowadays, individuals express experiences and opinions through online reviews. These has an influence on online marketing and obtaining real knowledge about products and services. However, some of the online reviews can be unreal. They may have been written to promote low-quality products/services or sabotage a product/service reputation to mislead potential customers. Such misleading reviews are known as spam reviews and require crucial attention. Prior spam detection research focused on English reviews, with less attention to other languages. The detection of spam reviews in Arabic online sources is a relatively new topic despite the relatively huge amount of data generated. Therefore, this paper contributes to such topic by presenting four different Arabic spam reviews detection methods, while putting more focus towards the construction and evaluation of an ensemble approach. The proposed ensemble method is based on integrating a rule-based classifier with machine learning techniques, while utilizing content-based features that depend on N-gram features and Negation handling. The four proposed methods are evaluated on two datasets of different sizes. The results indicate the efficiency of the ensemble approach where it achieves a classification accuracy of 95.25% and 99.98% for the two experimented datasets and outperforming existing related work by far of 25%.

Recent improvements in the fused filament fabrication (FFF) technique have extended its usage for the manufacturing of finished products in a variety of engineering fields. However, some challenges are to be overcome including moderate mechanical, thermal, and physical properties of finished products. This paper reviews ways of improving these properties during three phases of manufacturing namely pre-processing phase, in-situ/on-site processing phase, and post-processing phase. A systematic review of these three phases is not much explored in the additive manufacturing process and hence there is a lot of scope for innovation in improving the quality of the finished product. Results of the review are finally concluded and it is found the approaches presented here in this paper resulted in increasing the performance of the fabrication process and allow for the fabrication of products with better mechanical, thermal and physical capabilities.

Life in the current era of technology is almost every line connected to the internet, as well as when doing business. Website is a container used for business development and improvement. One form of this is to create an attractive website display as a strategy to increase product quality and quantity. This research aims to; 1) The creation of a marketing information system facility with the application of CRM using the web-based React.JS framework as the main purpose of the research, and 2) Understanding and describing the benefits of implementing a Marketing Information System with CRM Applications using the web-based React.JS framework as a marketing strategy to improve quality and product quantity. To implement this research, the researcher uses the Agile method. A website-based marketing system with the implementation of Customer Relationship Management (CRM) at Reswara Digital printing produces structured and detailed data storage and the delivery of product information to consumers can be carried out optimally.

The Internet of Things (IoT) foresaw a transparent network between the real and virtual worlds. IoT offers a promising potential to develop strong market and industrial applications. The export-oriented economy of industrial manufacturers relies on product and service creativity to retain a competitive advantage. The IoT-based applications of innovative manufacturing companies (IOTs), where most companies are involved and engaged in many of the case IoT-based applications, is motivated by computing capacity, networking, cost reduction and electronic components. A common motive is the Internet of Things applications and the improvement of after-sales service activities. The suggested Linear Product Design Regression (LPDR) algorithm classifies business product innovation design based on consumer input to support business development. Businesses, companies and the technology industry: the inhibitors hinder the development of the four IT applications. IoT offers one of the latest innovations in manufacturing to allow us to meet key challenges. The product design and development engineering are engaged in utilizing the Internet of Things (IoT) to create comprehensive policies and policy creation for manufacturing companies.To support business development. Businesses, companies and the technology industry: the inhibitors hinder the development of the four IT applications. To allow us to meet key challenges and to create comprehensive policies and policy creation for manufacturing companies.

Growing population and depleting resources are forcing the manufacturers to become more competent and sustainable. Customers are becoming more and more informed about the product they consume, and therefore, manufacturers need to be flexible and open to new changes taking place. Big Data Analytics (BDA) is one such technology that has transformed the manufacturing sector. Organizations have now become more flexible with regards to their processes and, at the same time, have also improved their product quality. Here in this paper, we have analyzed various advantages of Big Data that manufacturing organizations can exploit for their betterment. We have also discussed examples of certain leading manufacturers and how they can lead to big data-enabled manufacturing. Lastly, we discuss certain shortcomings that need to be addressed to make big data analytics viable for organizations of all sorts and not just for top manufacturers.

Consider a market with two substitute products and a sequence of consumers. The consumers are uncertain about the quality of each product but obtain some private information about it. Additionally, each consumer observes the purchase decisions of her predecessors but not their private information. Absent prices, the standard logic of herding is that all but finitely many consumers may, with positive probability, select the lower quality product. One perspective in the literature is that informationally efficient market prices can resolve the herding inefficiency and induce asymptotic learning where the beliefs of consumers about product qualities converge to the truth. This paper shows that, while informationally efficient prices induce asymptotic learning, they also inflict a welfare cost. That is, we show that the expected welfare is decreasing in the frequency with which prices are set to be informationally efficient.

Problem definition: An on-demand service platform relies on independent workers (agents) who decide how much time, if any, to devote to the platform. Some labor advocates have argued that an expansion of the labor pool hurts agents—by reducing the wage and agent utilization (i.e., the fraction of time an agent is busy serving customers). Motivated by concern for agent welfare, regulators are considering measures that reduce the labor pool size or that impose a floor on the nominal wage or effective wage (i.e., the product of the nominal wage and agent utilization). Are agents indeed hurt by an expansion in the labor pool size? Which type of wage-floor regulation is preferable? Are consumers hurt by the imposition of a wage floor? Academic/practical relevance: Because independent agents work without the traditional protections intended to ensure the welfare of employees, the welfare of those agents is an important concern. Methodology: We employ an equilibrium model that accounts for the interaction among price, wage, labor supply, customer delay, and demand. Results: Average labor welfare increases and then decreases in the labor pool size; that is, agents are harmed by an expansion in the labor pool size if and only if the labor pool size is sufficiently large. The effective wage floor is superior to the nominal wage floor in terms of labor welfare maximization. More generally, the two types of wage floors have structurally different effects on labor welfare, with a floor on the nominal wage only beneficial to agents if it is sufficiently small. Contrary to the conventional view that consumers are hurt by an effective wage floor (because they face a higher price, due to upward pressure on the wage, and longer delay, due to upward pressure on agent utilization), consumers actually benefit. Managerial implications: Regulators, labor advocates, platform managers, and agents benefit from understanding the forces that create and destroy labor welfare.

We examine the impact of China's adoption of the logistics service standardization (LSS) as an exogenous shock on firm innovation. The results show that patents obtained by firms located in LSS cities after the reform increased more significantly compared to firms located in non-LSS cities. The findings are robust to alternative types of patents obtained, the number of patent applications, propensity score matched samples, accounting for selection bias, and placebo tests. Additional analyses suggest that the channels for the positive impact of the LSS on innovation are enhanced product market competition, lowered financial constraints, and reduced operating risk. In cross-sectional analyses, we document that the positive impact of the LSS on innovation is more salient for firms with distant supply chain partners, low inventory turnover, low production efficiency, high product potential, large government subsidies, and more bank loans.

Machine’s condition is very important for industry’s efficient organization, growth, sustainability in the market and to increase profit margin. Condition monitoring indicates possible forthcoming failure well in advance before it becomes extensive serious issue. By the use of this maintenance strategy machines performance, quality of product as well as life of machines also gets improved. In condition monitoring, worn out parts will be identified and remedial actions i.e. repairing or replacement can be suggested. There are so many methods used for condition monitoring such as visual monitoring, temperature monitoring, lubricating oil monitoring, crack and leakage detection, vibration monitoring, corrosion of parts monitoring. From all these methods, used lubricating oil monitoring along with ferrography gives nanotribological results about real time machine condition. The data obtained from this monitoring, calculates risk priority number which gives information regarding probability of machine failure. Risk priority number finds all causes leads to failure. This number is also used to rank the failure causes and also suggests remedial measures. Hence wear monitoring followed by risk priority number to improve machines functionality and efficiency.

In his 1962 NBER volume, The Growth of Industrial Production in the Soviet Union, Warren Nutter writes about how the study of the Soviet economy was hamstrung by official secrecy and data limitations. Western economists were forced to rely on what Nutter called “Marco Polo economics” or “travelers' tales” to replace or interpret quantitative data. Nutter's book is littered with these tales of Soviet economic activity from Soviet émigrés, foreign visitors, and reports of Soviet citizens. The tales provide a narrative grounding for The Growth of Industrial Production in the Soviet Union by outlining the flow of data through the Soviet statistical bureaucracy, establishing the strengths and limitations of Soviet data, and aiding in the interpretation of difficult-to-measure concepts such as product quality and military production.

I study how a firm manages its reputation by both investing in the quality of its product and censoring, hiding bad news from consumers. Without censorship, the threat of bad news provides strong incentives for investment. I highlight discontinuities in the firm’s maximum equilibrium payoff that censorship creates. When censorship is inexpensive, the firm never invests and a patient firm’s payoffs approach the lowest possible. In contrast, when censorship is moderately expensive, there exist equilibria where product quality is persistently high and payoffs approach the first-best, which can exceed the maximum equilibrium payoff if it was unable to censor. (JEL D21, D82, D83, G31, G32, L15)

This paper analyses the impact of economic complexity on the labour market using annual data on OECD countries for the period 1985-2008 and averaged data over the period 1990-2010 for 70 developed and developing countries with a large number of controls. We show that moving to higher levels of economic sophistication of exported goods leads to less unemployment and more employment, revealing that economic complexity does not induce job loss. Our findings remain robust across alternative econometric specifications. Furthermore, we place the spotlight on the link between products' embodied knowledge (sophistication) and labour market outcomes at the micro-level. We build a product-level index that attaches a product to the average level of unemployment (or employment) in the countries that export it. With this index, we illustrate how the development of sophisticated products is associated with changes in the labour market and show that the economic sophistication of exported goods captures information about the economy's job creation and destruction., Economics of Innovation and New Technology, 32 (1), ISSN:1043-8599, ISSN:1476-8364

Start-ups are confronted with a particularly tricky issue: when and by how much to build up production or service capacity. In its early stage, the priority of a start-up is customer and product development. Without a concrete product and a concrete customer, it’s risky to divert scarce financial and management resources to production capacity. On the other hand, once the product is developed and some customer wants to buy it, then production capacity needs to be in place to deliver. This high uncertainty if and when demand starts to grow results in a behavior pattern called growth and underinvestment. While demand grows, the capacity to deliver lags behind. Typically, if capacity is insufficient to meet demand properly, this results in a growing backlog or decreasing quality. Either way, customer satisfaction deteriorates, resulting in shrinking demand. Because of shrinking demand, there is now more than enough capacity. The difference between revenues and expenditure results in a negative cash flow. By the same token, when the backlog shrinks, quality might improve. If the start-up survives its financial crisis and is still in business, then demand grows again, but not all lost customers will come back. This dynamics is shown in Fig. 14.1.

The food chain is made up of the different stages that the product follows from its origin to its final destination: production, transformation, storage, distribution and consumption. Throughout the chain, the traceability of the food is key to alert of any potential danger, establishing comprehensive food safety, from the beginning to the end, “from farm to fork". The transformation that is taking place in society thanks to the most avant-garde information and communication technologies (ICTs), is also breaking into the food chain, constituting the food industry 4.0, which is available at the service of each link through intelligent systems that allow obtaining safer, higher quality products in less time. Each ICT will offer different development possibilities thanks to its particular characteristics, so that in each link the most appropriate technology will be selected to solve the specific problems posed. This work aims to carry out a review of all these avant-garde tools, describing how thanks to these disruptive technologies, the processes of the food chain are being transformed, increasing, at the same time, the safety and quality of the products obtained and evaluating the possible associated social repercussions. Keywords: Information and Communication Technologies (ICTs), Food Chain, Industry 4.0, Artificial Intelligence, Smart Packaging. doi: https://doi.org/10.36825/RITI.09.19.004