The Role of Trust in European Food Chains: Theory and Empirical Findings

In Europe, consumer trust in food has become one of the most important factors for the stability of the food sector. An essential prerequisite for the ability to communicate the trustworthiness of food to consumers (B2C) is the creation, maintenance, and communication of trust between companies across the entire food value chain (B2B). For the management and preservation of trust in food chains it is important to know whether differences occur across European countries or whether distinct product chains show variations regarding trust. Based on a survey in five European countries with 747 respondents, this paper assesses the current level of trust between companies together with its influencing structural factors in European food chains and determines criteria allowing the active management of the level of trust in business relations in food chains by estimating a structural equation model.trust, levels of trust, determinants to trust, food chain management, trust management, Agribusiness, Food Consumption/Nutrition/Food Safety,

The Role of Task Technology Fit to Enhance Student Satisfaction Towards Blended Learning in Chengdu, China

Purpose: Blended learning had become a popular educational approach that mixed the characteristics of face-to-face lectures and online learning in the digital age. This research aimed to examine the factors of task technology fit, confirmation, cognitive presence, teaching presence, social presence, and learner-instructors interaction to impact blended learning satisfaction of college students in Chengdu, China. The research model demonstrates relationships between key varaibles. Research design and methodology: This research applied the quantitative method and questionnaire as instruments to survey 500 students, who majored in art and design subjects. Before distributing the questionnaires, Item-Objective Congruence (IOC) and a pilot test of Cronbach’s Alpha were used to test validity and reliability. Data was analyzed by utilizing Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM) to validate the model’s goodness of fit and confirm the causal relationship among variables for hypothesis testing.. Results: The main findings revealed that confirmation, cognitive presence, social presence, and learner-instructors interaction significantly influenced satisfaction with blended learning, except task technology fit and teaching presence. Cognitive presence and learner-instructor interaction has strong and significant role to enhance students’ satisfaction with hybrid learning. Conclusions: The study has found that the research conceptual model could predict and explain how the factors impact blended learning satisfaction

Customer Participation in Digital Transformation, Value Co-Creation and Firm Performance: An Empirical Study in China Information Communication & Technology Industry

The role of customer participation is an important area in service marketing research. Increasingly more enterprises encourage customers to participate in the service production and delivery processes, stimulate customers to share innovative ideas, and promote a greater role for customers through participation. Although some research has acknowledged the importance of customer participation in creating knowledge and value for enterprises, it has ignored the uncertainty and the complexity that customer participation may bring. Most scholars study customer participation only in a broad sense without examining how to effectively manage customer participation. To address this existing research deficiency, this study uses service-oriented logic, digital transformation theory, value co-creation theory, and corporate performance theory to examine how enterprises can promote customer participation in the process of digital transformation, co-create corporate value with customers, improve and influence the company's digital transformation maturity, and thus promote the company's performance growth (including environmental, economic, and relationship performance). Specifically, this study makes the following major contributions: 1. Based on the behaviour of customers participating in digital transformation, customer participation is divided into four dimensions (information and knowledge exchange, business collaboration, co-leading, and cost-effectiveness) to understand the process of value co-creation, and to some extent, resolve the inconsistent views of customer participation in existing research. Most extant studies explore customer participation as a whole; such integrated research results in the loss of customer participation’s rich connotation and leads to differing opinions about the impact of customer participation. 2. Based on the theory of digital transformation and the theory of digital maturity model, this study primarily examines how to effectively guide and manage customers from the perspective of an operational management model and strategy. The existing research on value co-creation largely focuses on how external environmental factors influence value co-creation among enterprises. These factors are difficult for enterprises to control and control. 3. This study focuses on the co-creation results of traditional enterprise customers and Internet enterprise customers in the process of digital transformation, analyses and compares the different concerns of traditional enterprise customers and Internet enterprise customers on the value co-creation process, and provides effective and positive aid for future strategic planning regarding these two types of customers. The information communication technology industry in China is taken as this study’s research object; five representative enterprises are selected. First, 10 traditional enterprise customers, Internet enterprise customers, and industry experts are interviewed in-depth, and the questionnaire is collected. Second, 506 matching questionnaires for traditional enterprise customers and Internet enterprise customers were collected. Using structural equation modelling, this study examines the relationship between digital transformation and corporate value co-creation, as well as the intermediate role of digital maturity on digital transformation and corporate value co-creation. The empirical results support most of the assumptions, as follows: 1. Customer participation in digital transformation has a significantly positive impact on value co-creation (economic, innovation, and relationship value). 2. Value co-creation (economic, innovation, and relationship value) has a significantly positive impact on firm performance. 3. Digital transformation maturity has a significant moderating effect on the influence of value co-creation on firm performance. 4. Value co-creation has a mediating effect on the relationship between customer participation in digital transformation and firm performance

Distance,Time and Terms in First Story Detection

First Story Detection (FSD) is an important application of online novelty detection within Natural Language Processing (NLP). Given a stream of documents, or stories, about news events in a chronological order, the goal of FSD is to identify the very first story for each event. While a variety of NLP techniques have been applied to the task, FSD remains challenging because it is still not clear what is the most crucial factor in defining the “story novelty”. Giventhesechallenges,thethesisaddressedinthisdissertationisthat the notion of novelty in FSD is multi-dimensional. To address this, the work presented has adopted a three dimensional analysis of the relative qualities of FSD systems and gone on to propose a specific method that wearguesignificantlyimprovesunderstandingandperformanceofFSD. FSD is of course not a new problem type; therefore, our first dimen sion of analysis consists of a systematic study of detection models for firststorydetectionandthedistancesthatareusedinthedetectionmod els for defining novelty. This analysis presents a tripartite categorisa tion of the detection models based on the end points of the distance calculation. The study also considers issues of document representation explicitly, and shows that even in a world driven by distributed repres iv entations,thenearestneighbourdetectionmodelwithTF-IDFdocument representations still achieves the state-of-the-art performance for FSD. Weprovideanalysisofthisimportantresultandsuggestpotentialcauses and consequences. Events are introduced and change at a relatively slow rate relative to the frequency at which words come in and out of usage on a docu ment by document basis. Therefore we argue that the second dimen sion of analysis should focus on the temporal aspects of FSD. Here we are concerned with not only the temporal nature of the detection pro cess, e.g., the time/history window over the stories in the data stream, but also the processes that underpin the representational updates that underpin FSD. Through a systematic investigation of static representa tions, and also dynamic representations with both low and high update frequencies, we show that while a dynamic model unsurprisingly out performs static models, the dynamic model in fact stops improving but stays steady when the update frequency gets higher than a threshold. Our third dimension of analysis moves across to the particulars of lexicalcontent,andcriticallytheaffectoftermsinthedefinitionofstory novelty. Weprovideaspecificanalysisofhowtermsarerepresentedfor FSD, including the distinction between static and dynamic document representations, and the affect of out-of-vocabulary terms and the spe cificity of a word in the calculation of the distance. Our investigation showed that term distributional similarity rather than scale of common v terms across the background and target corpora is the most important factor in selecting background corpora for document representations in FSD. More crucially, in this work the simple idea of the new terms emerged as a vital factor in defining novelty for the first story

Coverage & cooperation: Completing complex tasks as quickly as possible using teams of robots

As the robotics industry grows and robots enter our homes and public spaces, they are increasingly expected to work in cooperation with each other. My thesis focuses on multirobot planning, specifically in the context of coverage robots, such as robotic lawnmowers and vacuum cleaners. Two problems unique to multirobot teams are task allocation and search. I present a task allocation algorithm which balances the workload amongst all robots in the team with the objective of minimizing the overall mission time. I also present a search algorithm which robots can use to find lost teammates. It uses a probabilistic belief of a target robot’s position to create a planning tree and then searches by following the best path in the tree. For robust multirobot coverage, I use both the task allocation and search algorithms. First the coverage region is divided into a set of small coverage tasks which minimize the number of turns the robots will need to take. These tasks are then allocated to individual robots. During the mission, robots replan with nearby robots to rebalance the workload and, once a robot has finished its tasks, it searches for teammates to help them finish their tasks faster

Inquisitive Pattern Recognition

The Department of Defense and the Department of the Air Force have funded automatic target recognition for several decades with varied success. The foundation of automatic target recognition is based upon pattern recognition. In this work, we present new pattern recognition concepts specifically in the area of classification and propose new techniques that will allow one to determine when a classifier is being arrogant. Clearly arrogance in classification is an undesirable attribute. A human is being arrogant when their expressed conviction in a decision overstates their actual experience in making similar decisions. Likewise given an input feature vector, we say a classifier is arrogant in its classification if its veracity is high yet its experience is low. Conversely a classifier is non-arrogant in its classification if there is a reasonable balance between its veracity and its experience. We quantify this balance and we discuss new techniques that will detect arrogance in a classifier. Inquisitiveness is in many ways the opposite of arrogance. In nature inquisitiveness is an eagerness for knowledge characterized by the drive to question to seek a deeper understanding and to challenge assumptions. The human capacity to doubt present beliefs allows us to acquire new experiences and to learn from our mistakes. Within the discrete world of computers, inquisitive pattern recognition is the constructive investigation and exploitation of conflict in information. This research defines inquisitiveness within the context of self-supervised machine learning and introduces mathematical theory and computational methods for quantifying incompleteness that is for isolating unstable, nonrepresentational regions in present information models

Key success factors facilitating SME ecommerce in developing countries : evidence from Indonesia

This research is mix method research (qualitative and quantitative) which have two main objectives observing the evidence from Indonesia. Firstly, to identify the key success factors facilitating SME ecommerce in developing countries especially in post-adoption stage of ecommerce practice. Secondly, to examine the relationship among the logistics capabilities (internal, external and country logistics capabilities) and the SME ecommerce transaction. Besides, the research also attempted to identify the major logistics problems faced by logistics sector and also to clarify the country logistics performance index, both investigations are related to the SME ecommerce practice.The SLR has identified seven potential key success factors facilitating SME ecommerce in developing countries which has been categorized into three factors including internal, external and interconnected factors. Internal factors included human resources and marketing/marketplace decision. External factors comprised customer demand, law and regulation, and secure payment system. Meanwhile the interconnected factors involved information and communication technology (ICT) and logistics capabilities. Firming these findings, the interview study accomplished towards seven SMEs ecommerce in Indonesia which indicated the similar factors based on their experiences and practices. Moreover, the second phase of the research has administered the collection of questionnaires toward 372 respondents involving the industries, governments, academicians, logistics associations, logistics service providers (LSPs), and SMEs ecommerce. The weight analysis of the research has identified the five major problems of logistics sectors in Indonesia related to the SME ecommerce which included the problems of infrastructures, road traffic jam level, government law and regulations, human resources and also dwelling time in port. Besides, the research also observed the Indonesia Logistics Capability Index (ILCI) concerning the SME ecommerce practice which clarified the index slightly above the average level (score: 2.79 out of 5). Furthermore, the last phase of the research has accomplished through the operation exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and covariance-based structural equation modelling (CB-SEM). It has examined that internal logistics capabilities showed a respectable relationship to SME ecommerce transaction, while external logistics capabilities indicated a modest relationship to SME ecommerce transaction, yet it is still tolerable. In the other hand, even though the country logistics capabilities indicated a poor relationship to SME ecommerce transaction, but it has a very supported effect toward external logistics capabilities and external logistics capabilities.The findings of the research effectively contribute to both theory and practice and the research propositions provide potential and applicable guidance for the stakeholders in academia, companies and government to facilitate SME ecommerce development in developing countries especially in Indonesia related to the entire logistics capabilities

Digital transformation readiness : perspectives on academia and library outcomes in information literacy

This study examines the readiness of a faculty for the social challenges caused by the digital transformation in academia with the use of covariance-based structural equation modeling (CBSEM). Based on the survey results, we have examined the interplay between factors related to digital transformation. The concepts of information literacy and digital literacy related to academic librarianship were used as the basis for the self-efficacy and empowerment necessary to achieve individual success during digital changes in the academic community. We then checked how such a sense of empowerment among academics explains the presence of information culture in this community and different approaches to information management. The factors of information management and information use were presented as affecting a university's institutional readiness for the new requirements of digital transformation from the perspective of governance issues. The findings highlight that information literacy underlies academics' empowerment and a high level of self-efficacy driven by this literacy can also be indirectly translated into the formation of pro-active information culture that strengthens an academic's position in creating information use outcomes and by making them ready for digital transformation. Through information literacy outcomes the academic libraries can turn out to be an important transformative force in terms of digital changes at universities