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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.

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.

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.

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.

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.

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%.

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.

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.

Reliability-centered maintenance (RCM) determines the maintenance needs of any facility, system, or equipment in its operating context. RCM, systematically, identifies the preventive maintenance tasks required to sustain, in the most cost-effective manner possible, the maximum level of reliability and safety that can be expected from a product when it receives effective maintenance. The RCM process takes place first during the equipment design and development phase, when it is used to develop maintenance plans. During the product operation and deployment, these plans are modified based on field experience. The history of RCM began within the commercial aircraft industry in the late 1960s. A 1968 handbook titled “Maintenance Evaluation and Program Development,” prepared by the United States Air Transport Association (ATA) for use with the Boeing 747 aircraft, contained one of the earliest formal treatments of the subject. Two years later, a revised version of the handbook also discussed two other wide-body aircraft, the DC- 10 and the L- 1011. In 1974, when the United States Department of Defense commissioned United Airlines to prepare a document on civil aviation aircraft maintenance programs, the term “reliability-centered maintenance” was coined as the title of the resulting document. Today, RCM is used in the United Kingdom, Canada, the United States, Spain, Singapore, and Australia, among others.

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.

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.

The field's knowledge of marketing-mix elasticities is largely restricted to developed countries in the North-Atlantic region, even though other parts of the world—especially the Indo-Pacific Rim region—have become economic powerhouses. To better allocate marketing budgets, firms need to have information about marketing-mix elasticities for countries outside the North-Atlantic region. The authors use data covering over 1,600 brands from 14 product categories collected in 7 developed and 7 emerging Indo-Pacific Rim countries across more than 10 years to estimate marketing elasticities for line length, price, and distribution and examine which brand, category, and country factors influence these elasticities. Averaged across brands, categories, and countries, line-length elasticity is .459, price elasticity is −.422, and distribution elasticity is .368, but with substantial variation across brands, categories, and countries. Contrary to what has been suggested in previous research, the authors find no systematic differences in marketing responsiveness between emerging and developed economies. Instead, the key country-level factor driving elasticities is societal stratification, with Hofstede's measure of power inequality (power distance) as its cultural manifestation and income inequality as its economic manifestation. As the effects of virtually all brand, category, and country factors differ across the three marketing-mix instruments, the field needs new theorizing that is contingent on the marketing-mix instrument studied.

Cloud service providers promote their new field programmable gate array (FPGA) infrastructure as a service (IaaS) as the new era of cloud product. This FPGA IaaS wraps virtualized compute resources with FPGA boards, e.g., Amazon AWS F1, and reserves acceleration capability for specific applications. Though this acceleration technique sounds promising, questions like real-world performance, best-fit scenarios, portability, etc., still need further clarification. In this paper, we present one of the first few empirical studies that take a close look at FPGA clouds from the tenants' perspective. We have conducted measurement studies on Amazon AWS, Alibaba, and Huawei clouds for over one year. The experimental results show that: (1) Tenants experience severe performance-cost anomaly on FPGA IaaS platforms; (2) The inter-communication performance in FPGA clouds is tightly constrained by hardware drivers, e.g., small optimization of DMA drivers for PCIe can harvest significant performance gain; (3) The virtualized FPGA clouds are far from mature, e.g., small-sized jobs can greatly degrade the performance of FPGA clouds due to underutilized PCIe bandwidth. Our study not only provides useful hints to help tenants with FPGA service selection, but also sheds some lights for cloud providers to improve the performance of FPGA clouds.

Due to financial and temporal limitations, the small wind community relies upon simplified wind speed models and energy production simulation tools to assess site suitability and produce energy generation expectations. While efficient and user-friendly, these models and tools are subject to errors that have been insufficiently quantified at small wind turbine heights. This study leverages observations from meteorological towers and sodars across the United States to validate wind speed estimates from the Wind Integration National Dataset (WIND) Toolkit, the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5), and the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), revealing average biases within ±0.5 m s−1 at small wind hub heights. Observations from small wind turbines across the United States provide references for validating energy production estimates from the System Advisor Model (SAM), Wind Report, MyWindTurbine.com, and Global Wind Atlas 3 (GWA3), which are seen to overestimate actual annual capacity factors by 2.5, 4.2, 11.5, and 7.3 percentage points, respectively. In addition to quantifying the error metrics, this paper identifies sources of model and tool discrepancies, noting that interannual fluctuation in the wind resource, wind speed class, and loss assumptions produces more variability in estimates than different horizontal and vertical interpolation techniques. The results of this study provide small wind installers and owners with information about these challenges to consider when making performance estimates and thus possible adjustments accordingly. Looking to the future, recognizing these error metrics and sources of discrepancies provides model and tool researchers and developers with opportunities for product improvement that could positively impact small wind customer confidence and the ability to finance small wind projects.

Consumers may need help using an inherently complex or information-intensive product after purchase. This paper studies the incentive for a manufacturer or a retailer to invest in pre-sales service effort that would reduce the consumer's likelihood of seeking after-sales support. Because providing pre-sales and after-sales support would incur costs for the provider, it is not evident whether the manufacturer or the retailer would be more effective in doing so, and whether both services should be provided by the same firm. We consider different models in which the pre-sales service and the after-sales support is provided by the same or different firms, and show that the service configuration in which both pre-sales service and after-sales support is provided by the retailer is desirable to both the retailer and the manufacturer. Interestingly, in this service configuration, although the pre-sales service is provided at the highest level among all configurations, consumers can show up in the largest numbers to seek after-sales support. We also study the possibility of the firms collaborating in providing pre-sales service, by allowing the manufacturer to share a portion of the retailer's cost of providing pre-sales service. As expected, if the manufacturer provides the after-sales support, cost-sharing by the manufacturer may increase both channel members' profits. However, if the retailer provides after-sales support, cost-sharing by the manufacturer helps increase the manufacturer's profit but, surprisingly, reduces the retailer's profit. In this case, the overall channel can still be better off, and as such, the manufacturer may be able to implement cost-sharing by providing an appropriate transfer to the retailer.

Technologies transform the total marketing mix of hotel products in the dynamic tourism market, where the distribution is detected as a key factor of market placement and profitability. The main goal of this paper is to explore the distribution channels in the hospitality industry and to identify the most successful elements of online distribution for the purposes of realising future excellence in post-COVID-19 tourism. The online distribution elements that could enhance competitiveness and incentives for reservation were identified and ranked. This was realised by choosing the most representative sample and by researching it using a structured questionnaire, where the mix of competitiveness and marketing elements were evaluated. The research findings present the importance of online travel agents (OTA), tour operators, social networks and conferences (MICE segment). The potential of Global Distribution Systems (GDS) systems is detected and, although not fully valorised in practice, implicate future franchising and contracting with global hotel brands and consortia. The answer to the question: “Which tools and techniques of innovative online distribution should be used and what product elements enhance sales in the hotel industry of the future?” is explored by the scientific methodology, which supports the purpose and presents the main contribution of the paper. Implications for Central European audience: The paper represents a considerable contribution in the perception of the distribution channels, affirmed for exchange in the Central European tourism market as an emissive market for the receptive offer of Croatian tourism. Considered in the context of the accessibility of Croatia as a car destination that realises both long-term and short-term “impulsive” bookings, promptness, propulsion and dynamism of online distribution channels used by the hotel offer have exceptional importance for income management and profitability. Correspondingly, a positive perception is being developed of the Central European market demand, as well as tourism awareness about closeness and market potentials, which represents a platform for the development of applicative strategies in communication and business. Recognising the effect on intensification of tourist exchange through the affirmation of innovations and technology contributes to the development of science and practice of the hospitality industry.

High-utility itemset mining has evolved as an essential and captivating research topic. It aims to extract the patterns/itemsets having high utility value; hence, they are called high utility itemsets (HUIs). From a business perspective, a utility can be the benefit associated with the sale of a particular item or the usefulness or satisfaction that a customer experiences from a product. The economic utilities are helpful to evaluate the drivers behind a customer’s purchase decision. The advances in information technology have enabled us to access the datasets related to various domains like health care, stock market, market-basket, education and bioinformatics. Companies strive to increase the utility value of their products and share their customer’s transactions data to extract high utility patterns to achieve global customer insights. However, this can lead to massive security and privacy risk if their competitors misuse the patterns that can disclose their confidential information. Privacy-preserving utility mining (PPUM) is a branch of privacy-preserving data mining (PPDM) that presents various algorithms which intend to hide sensitive high utility itemsets (SHUIs) and maintain a balance between utility-maximizing and privacy-preserving. In this paper, two SHUIs hiding algorithms, MinMax and Weighted, are proposed with three variants of each algorithm. Experiments on various datasets show that proposed algorithms perform better than the existing SHUIs hiding algorithms as fewer distortions of non-sensitive knowledge occur. This study uses six performance evaluating metrics to assess the proposed algorithms against compared algorithms.

In 2014, Washington State used a lottery system to allocate licenses to firms in the newly legalized retail cannabis industry, generating random variation in how many stores entrepreneurs were able to own. We observe highly detailed data on all subsequent industry transactions, including prices, wholesale costs, markups, and product assortments. We find that entrepreneurs who are randomly allocated more store licenses ultimately earn substantially higher per store profits than do single-store firms, suggesting that the returns to scale in the mom-and-pop retail sector are quite large. Despite these firms having greater market power, this increase in profits does not come at the expense of consumers. Rather, retailers in multi-store chains ultimately charge significantly lower prices and margins and offer greater product variety. This gap in prices is not initially present but grows substantially over time, as does the difference in assortment size and profits between stores in multi-store chains and stores operating alone. Using the full history of outcomes, we track the evolution of firms in this new market and show that multi-store retailers use an initial advantage in offering larger assortments to position themselves as the low-price, large-assortment retail option and attract a larger but more price-sensitive set of customers. These results have implications for the study of retail concentration and mergers, countervailing buyer power, and consumer search. Our results suggest that policies to help entrepreneurs expand in retail may have large benefits to both firms and consumers.

Background aims The novelty of cell and gene therapies (CGTs) has introduced unique supply chain challenges and considerations not seen by chemically synthesized (small-molecule) drugs. These complexities increase during the clinical phases, where drug safety and efficacy milestones are still underdeveloped. For example, for autologous therapies such as chimeric antigen receptor T-cell therapies, in which the treatment is developed from the patient's own cells, supply chain management plays an integral role in chemistry, manufacturing and control processes. Supply chain management requires proactive planning because of the strict cold chain requirements and time sensitivity of CGTs. This research examines strategies and responses to challenges experienced by industry stakeholders (e.g., sponsors and manufacturers) during the implementation phases of clinical supply chain management. This research further evaluates the adequacy of the current regulatory framework for distribution and supply chain management of CGTs in the US. Methods A survey methodology was used to query subject matter experts from the biopharmaceutical industry who were familiar with the clinical supply management of CGTs in the US. The survey instrument was developed using an implementation framework and disseminated electronically to mid- and senior-level subject matter experts who had experience with clinical trials, supply chain management and CGTs. Results A total of 128 respondents accessed the survey, and 105 respondents answered at least one question. Seventy-five respondents completed the survey. Results showed that a lack of harmonization in regulations across the supply chain, limited resources, challenges with vendor management, high costs and complexities in the supply chain due to product specificity and customization proved to be impediments for the industry. In addition, the coronavirus disease 2019 pandemic had a significant impact on supply chain implementation. The results revealed that less than half of the respondents had business continuity plans in place. These challenges increased for smaller and mid-size organizations. Thirty percent of small and mid-size organizations were less prepared to scale up than larger companies. Conclusions Suggestions from industry stakeholders were to adopt and enforce Good Distribution Practices in the US (81%), pre-plan distribution strategies with internal and external stakeholders along the supply chain and develop agile systems and robust processes end to end. Hurdles in scaling up and scaling out from the clinical to commercial phases for time- and temperature-sensitive CGT products make it difficult to predict the supply chain's long-term feasibility. Although there are initiatives to improve these impediments, such as improving industry partnerships and creating global CGT transportation standards, there are still regulatory knowledge gaps present for CGTs. Therefore, it is essential to establish a baseline and foundation for CGT supply chains extending beyond the loading dock.

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.

У публікації висвітлена проблема розповсюдження сумішей для паління спайс на території країн Євросоюзу та окремих країн Східної Європи за останнє десятиріччя. Акцент зроблено на недостатню ефективність заходів щодо контролю обороту сумішей для паління, що були реалізовані в державах — членах Європейського Союзу за останні 10 років. Розглянута історія розробки синтетичних канабіноїдів і токсикологічна характеристика речовин JWH, СР, HU, олеаміду як найбільш поширених синтетичних продуктів із канабіноїдною активністю. Проаналізовані біологічна активність і медичні наслідки вживання продуктів спайс за даними тематичних звітів дослідницьких центрів країн Євросоюзу та США. Розглянута роль сучасної маркетингової стратегії виведення на ринок продуктів спайс, зокрема особливості реалізації продуктів через систему Інтернет в Україні.Проаналізована токсикологічна ситуація, що склалася в Україні за останні роки через поширення «дизайнерських» наркотиків, яка характеризується масштабною рекламою трав’яних сумішей у мережі Інтернет; широким необмеженим доступом до зазначених продуктів у пунктах роздрібної торгівлі, де суміші спайс реалізуються найчастіше під виглядом лікарських засобів альтернативної медицини або харчових добавок і мають помірно невисоку ціну; поширенням практики вживання токсичних наркотичних речовин серед підлітків і молоді; прогресивним збільшенням кількості передозувань та смертельних отруєнь в окремих регіонах України за останні роки. В цьому контексті визначена ключова роль державного регулятора в розробці запобіжних заходів щодо фатальних наслідків застосування сумішей спайс серед молоді на прикладі досвіду окремих країн.Авторами надані пропозиції до негайного об’єднання зусиль уповноважених державних органів (Міністерства охорони здоров’я та відомчих науково-дослідних установ, Міністерства внутрішніх справ, Служби безпеки України та інших зацікавлених служб) з метою розробки державної стратегії та прий­няття управлінських рішень щодо заборони продуктів спайс (і подібних) або суттєвого обмеження їх продажу на території України.

The furniture business has developed quite well every year, but the promotions used by the company still use the usual methods, such as using brochures that only display 2D information and images. With so much competition, consumers want something unique and different so they can find out more detailed and real product information offered. Augmented reality is the right technology to meet these consumer needs. Augmented reality is a technology that combines the virtual world with the real world directly. Therefore, an application was designed that functions as a company profile as well as displays 3D rattan chair products using Augmented reality technology on android devices. The method used in this research is the Multimedia Development Life Cycle (MDLC) which includes Concept, Design, Material Collecting, Assembly, Testing, and Distribution. This Augmented reality application requires streaming video taken from a smartphone camera as an input source, then this application will track and detect markers using a tracking system, after the marker is detected, the 3D chair model in the catalog will appear above the marker as if it were a chair model. it's real. the results of the hypothesis test with a significant level of 0.139, which is greater than 0.05, then what is accepted is H1. It can be stated that an augmented reality-based electronic catalog application can increase buying interest in potential consumers of Raffi cushion rotan

Kuningan Regency is the area that has potential in agriculture. One of the leading commodities in Kuningan Regency is sweet potato (Ipomea batatas L). Sweet potato cultivation continues to be developed, even in Cilimus District, it is known as one of the productive production centers in the West Java region which provides sweet potato supplies to several areas to supply sweet potato needs in the West Java region. The problems are faced by farmers today including the increasingly erratic price of sweet potatoes, lack of market opportunities, product diversification, and mastery of cultivation technology. This service activity was carried out in Cilimus Village, Cilimus District, Kuningan Regency with partners of sweet potato farmers. The purpose of this assistance is to provide supply chain assistance for sweet potato marketing so that farmers are able to continuously market sweet potatoes above the production price. Mentoring activities were started from identification of sweet potato problems at the farmer level, identification of production and identification of markets. The using of method is interactive discussion and market mapping conducted together with farmers. Focus Group Discussion (FGD) was used to confirm the cultivation system, production, and marketing system of sweet potato. The result of this activity is that farmers know the marketing potential of sweet potatoes other than middlemen and the quality criteria of sweet potatoes according to industry demand. In addition, farmers also use sweet potatoes as animal feed.

In this paper, I empirically study the effect of chain affiliation on product variety and price in the movie theater industry. Using longitudinal data on Korean movie theaters, I find that movie variety in a theater increases by 3.2-5.5 percent after the theater joins a chain. Admission price, however, does not change after chain affiliation, implying that consumers benefit from the organizational form change. These results are consistent with the growing dominance of chain-affiliated theaters in recent decades. The results also suggest that the regulatory authorities should carefully examine the trade-off between increase in market power and efficiency gains when evaluating the implications of chain affiliation.

The aim of this research is to determine the commercial and environmental attractivity of solar panels applied to ships. In this case, a 40 m short route ferry is converted to a solar-electric operating in the Strait of Messina. The powering configuration of the ship is modelled, and a simulation is run using MATLAB. Finally, after the results were found, the solar-electric ship's powering costs and environmental impact using the Life Cycle Assessment method with the help of GaBi, were compared to a fully electric and a diesel alternative. GaBi is a very useful software to perform LCAs as it provides a very large database on various product’s emissions which can be modulated depending on their quantity. The results were encouraging as approximately 400,000 € were saved when using solar panels compared to only electricity and 500,000 € when comparing to diesel. Moreover, an observable reduction in the emissions in the solar-electric alternative. Remarkably, the electricity in the national grid produces a non-negligible impact on the environment. Therefore, any device which produces zero emissions but is powered by electricity coming from the national grid like an electric car is far from being emissions-free. On the other hand, the electricity coming from solar panels is close to being totally green and should all the electricity be coming from them if future advances on this technology are made, then the vehicle can be considered eco-friendly. The numerous advantages of solar panels in short route ferries observed in this research could lead to the replacement of the traditional oil powered ferried creating a huge positive impact on the environment. When looking at the future, some thought should be given the recycling of solar panels in order to stop our impact on the environment.

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.

Official prices are commonly publicized by firms as reference prices to influence consumers’ valuation of products. By characterizing the reference effect as a general nondecreasing concave function of the official price, we study the timing of pricing decisions in dual distribution channels where a manufacturer distributes the product by a direct channel and an indirect retail channel. We investigate two fundamental pricing policies wherein the manufacturer and the retailer put forward their selling prices simultaneously (ST) or sequentially (SQ). Counter intuitively, our analytical results demonstrate that despite facing a more severe downstream price competition, the manufacturer should charge a higher (rather than a lower) official price in the ST setting than in the SQ setting. In addition, with the reference effect of official price, the ideal case for the manufacturers that operate dual distribution channels is to let the direct channel focus on promoting products and let the retail channel function be the major selling channel, an idea which is supported by the practices of Nike, Apple, and many other leading brands around the world. Furthermore, our numerical examples disclose that the dual-channel efficiency under both decentralized cases (i.e., ST and SQ) increases in the magnitude and variability of the reference effect and the retail channel cost, but decreases in the unit direct channel cost. Finally, we extend our model to incorporate an online direct channel and an offline retailer. We find that, under all of CE, ST and SQ scenarios, the shipping fee charged in the online direct channel will reduce the manufacturer’s total profits by lowering her optimal official prices and direct-sales quantities simultaneously. Managerial implications of this study are discussed.

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.

This paper analyzes partnerships between foreign and domestic firms as a source of signaling advantages, considering the case of virtual codesharing in aviation. Virtual codesharing is an important type of cooperative agreement between airlines that does not change any real product attributes and hence provides the opportunity to identify this signaling effect. Roughly 75% of the flights in trans-Atlantic and Pacific markets involves codesharing. Typically, the consumer buys the ticket with the domestic airline, while a foreign airline operates the flight. Analyzing individual-level choice data from a representative sample of Australian air travelers, we find that the average consumer is willing to a pay a premium between 4 and 5.5% of the ticket price when a flight by a foreign carrier is codeshared with the national carrier Qantas. When flying to a less familiar destination, risk averse consumers are willing to pay a premium about two times higher than non-risk averse consumers, suggesting that partnerships have a strong impact on consumer valuation through reducing perceived risks and uncertainties associated with alien carriers. By this mechanism, home country bias may spillover to foreign partners of domestic firms.

Industry 4.0 encourages the combination of latest technologies and manufacturing systems. The Additive Manufacturing (AM) may play a fundamental role in Industry 4.0 as it has capability of turning a 3D model data into a product without much human intervention. Moreover, the requirement for eliminated tools and fixtures and material waste make it suitable for industry of the future. The 3D model data, generated using modeling software is utilized in order to fabricate a three-dimensional object. However, the modeling software has some limitations regarding the conversion of the 2D digital image into a 3D model. It makes difficult direct additive manufacturing of 2D digital image. Although, there are some online resources available for this purpose. However, the detailed discussion on the algorithm is not available. Therefore, this article presents an approach for additive manufacturing of lithophane using 2D digital image. It mainly concentrates on the development of Graphical User Interface (GUI) for generating point cloud data and STL using a 2D digital image in MATLAB environment. The developed algorithm is discussed in detail for lithophane fabrication. The proposed approach takes 2D digital image from the user and converts it into 3D model data. Furthermore, the material deposition tool path is also prepared using generated 3D model data. Finally, the proposed approach is validated and tested by performing additive manufacturing. The obtained results have shown the conformity between the additive manufactured lithophane and given a 2D digital image. The obtained results of the current study may be useful in industry 4.0 for fashion and jewelry products.

The COVID-19 has brought us unprecedented difficulties and thousands of companies have closed down. The general public has responded to call of the government to stay at home. Offline retail stores have been severely affected. Therefore, in order to transform a traditional offline sales model to the B2C model and to improve the shopping experience, this study aims to utilize historical sales data for exploring, building sales prediction and recommendation models. A novel data science life-cycle and process model with Recency, Frequency, and Monetary (RFM) analysis method with the combination of various analytics algorithms are utilized in this study for sales prediction and product recommendation through user behavior analytics. RFM analysis method is utilized for segmenting customer levels in the company to identify the importance of each level. For the purchase prediction model, XGBoost and Random Forest machine learning algorithms are used to build prediction models and 5-fold Cross-Validation method is utilized to evaluate their. For the product recommendation model, the association rules theory and Apriori algorithm are used to complete basket analysis and recommend products according to the outcomes. Moreover, some suggestions are proposed for the marketing department according to the outcomes. Overall, the XGBoost model achieved better performance and better accuracy with F1-score around 0.789. The proposed recommendation model provides good recommendation results and sales combinations for improving sales and market responsiveness. Furthermore, it recommend specific products to new customers. This study offered a very practical and useful business transformation case that assists companies in similar situations to transform their business models.

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.

This paper analyzes the relation between COVID-19, air pollution, and public transport mobility in the Mexico City Metropolitan Area (MCMA). We test if the restrictions to economic activity introduced to mitigate the spread of COVID-19 are associated with a structural change in air pollution levels and public transport mobility. Our results show that mobility in public transportation was significantly reduced following the government's recommendations. Nonetheless, we show that the reduction in mobility was not accompanied by a reduction in air pollution. Furthermore, Granger-causality tests show that the precedence relation between public transport mobility and air pollution disappeared as a product of the restrictions. Thus, our results suggest that air pollution in the MCMA seems primarily driven by industry and private car usage. In this regard, the government should redouble its efforts to develop policies to reduce industrial pollution and private car usage.

Management of supplier and raw material with respect to food safety is a complex task, yet it can be made simple by appropriate organizational and management culture. A food safety manager with the right culture, adequate formal education, and relevant experience would apply the available tools, such as good manufacturing practices, hazard analysis and critical control point, and audits to ensure the final safety of a product. Supplier performance and adherence to agreed specifications with regard to raw materials are key criteria to be managed in maintaining food safety. Continuous contact and review of supplier and raw material performance would lead to continuous improvement.

Since their discovery in 1961, liposomes have mainly been studied and applied to the fields of drug and gene delivery. However, as some research studies have shown, there is the potential for liposome application in the food, beverage, and neutraceutical industries. Unfortunately, to date, these research advances have been stuck in the small-scale phase as large-scale production and manufacturing of liposomes in food and beverages face grave issues that are often more costly to overcome than they are beneficial to the product they are trying to enhance. In this chapter, we will take a look at some of the studies that have been done on liposomes in the food and beverage industry and the problems that have been encountered in large-scale production. We will also take a look at one supplemental liposomal product and how attempts are being made to avoid the difficulties of commercialization.

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

I identify effects of financial constraints on firms' product pricing decisions, using a sample of insurance groups (conglomerates) that contain both life and P&C (property & casualty) subsidiaries. P&C subsidiaries' losses can tighten financial constraints for the life subsidiaries through internal capital markets. I present a model that predicts following P&C losses, premiums should fall for life policies that initially increase insurers' statutory capital, and rise for policies that initially decrease capital. Empirically, I find that P&C losses cause changes in life insurance premiums as my model predicts. The effects are concentrated in more financially constrained groups. Evidence also indicates that life subsidiaries increase capital transfers to P&C subsidiaries following larger P&C losses. These results hold when instrumenting for P&C losses using data on weather damages, implying that P&C losses do cause changes in life insurance premiums and internal capital transfers. My findings suggest that when financial constraints tighten, firms change product prices to relax the constraints, and how prices change depends on the initial impact of selling the products on firms' financial resources.