Narrow Results

The interface is a crucial element in component-based software, enabling the linkage of distinct components to facilitate interaction. Defects within the interface can significantly impact the overall trustworthiness of the system. Therefore, it is essential to assess the interface trustworthiness based on a defect-centric approach. This paper introduces a novel model for evaluating interface trustworthiness, anchored in defect analysis. First, the defect types are formalized based on interface specifications. Then, the comprehensive weight allocation method is established to characterize the importance degree of each interface defect type by combining the G1 and CRITIC methods. Subsequently, the attributes of the interface are evaluated by defect value analysis, and the trustworthiness measurement model of the interface is proposed based on these attributes. Furthermore, to evaluate the trustworthiness of the whole system, the trustworthiness measure models under different combination structure of components are established. Finally, the model’s’ applicability is demonstrated through an illustrative example. This trustworthiness evaluation from the interface view can guide interface designers to obtain high-quality interfaces and improve the trustworthiness of the entire software.

While trustworthiness is seen as an important factor in success of cluster development agents (CDAs), its antecedent competencies were not identified. Against this gap, the current study seeks to explore the scope and sequence of CDAs’ trustworthiness competencies, highlighting the importance of paying attention to cultivating those competencies. Conducting a number of semi-structured interviews as well as one Interactive Management (IM) session which was empowered by using Interpretive Structural Modelling (ISM) software, 6 trustworthiness competencies seem to be important for CDAs were identified, including: Proficiency, Altruism, Acceptability, Ability to alert stakeholders, Expectation identification ability, and Ability to make cooperation. More importantly, the interdependencies amongst those 6 competencies were identified and modelled, shedding light on the priority and weight of each of those competencies as antecedents of CDAs’ trustworthiness. As the theoretical implementation, this study expressed the importance of trustworthiness for CDAs and modelled the antecedent competencies which need to be obtained by CDAs if they are to be trusted by their clients. If a cluster clients do now trust their agent, they should not be blamed. The trustee need to cultivate those pre-requirement competencies if s/he wants to be trustworthy. As the practical implementation, the findings of this study provide a coherent curriculum for enhancing CDAs’ trustworthiness competencies. This curriculum should be implemented by the economic and development organisations who are dealing with training and preparing agents to take role in activating and extending industrial clusters in different countries.

Extracting useful knowledge from social network datasets is a challenging problem. While large online social networks such as Facebook and LinkedIn are well known and gather millions of users, small social networks are today becoming increasingly common. Many corporations already use existing social networks to connect to their customers. Seeing the increasing usage of small social networks, such companies will likely start to create in-house online social networks where they will own the data shared by customers. The trustworthiness of these online social networks is essentially important for decision making of those companies. In this paper, our goal is to assess the trustworthiness of local social network data by referencing external social networks. To add to the difficulty of this problem, privacy concerns that exist for many social network datasets have restricted the ability to analyze these networks and consequently to maximize the knowledge that can be extracted from them. This paper addresses this issue by introducing the problem of data trustworthiness in social networks when repositories of anonymized social networks exist that can be used to assess such trustworthiness. Three trust score computation models (absolute, relative, and weighted) that can be instantiated for specific anonymization models are defined and algorithms to calculate these trust scores are developed. Using both real and synthetic social networks, the usefulness of the trust score computation is validated through a series of experiments.

Various types of applications make access to objects distributed in peer-to-peer (P2P) overlay networks. Even if the locations of target objects are discovered by some look-up algorithm such as flooding and distributed hash table (DHT), applications cannot manipulate the target objects without access rights. It is critical to perceive which peer can manipulate an object in which method, i.e. only a peer authorized with an access right is allowed to manipulate an object. Hence, an application has to find peers which can manipulate a target object rather than detect the location of the target object. Due to the scalability, variety, and autonomy of peers, it is difficult, may be impossible to maintain a centralized directory showing in which peer each object is distributed. An acquaintance peer of a peer p is a peer whose service the peer p knows and with which the peer p can directly communicate. We discuss types of acquaintance relations of peers with respect to what objects each peer holds, is allowed to manipulate, and can grant access rights on. Acquaintance peers of a peer may notify the peer of different information on target peers due to communication and propagation delay. Here, it is critical to discuss how much a peer trusts each acquaintance peer. We first define the satisfiability of an acquaintance peer, i.e. how much a peer is satisfied by issuing an access request to the acquaintance peer. For example, if a peer p locally manipulates a target object o and obtains a response, p is mostly satisfied. On the other hand, if the peer p has to ask another peer to manipulate the object o, the peer p is less satisfied. We define the trustworthiness and ranking factor of an acquaintance peer obtained by accumulating the satisfiability of each interaction with the acquaintance peer. Differently from traditional reputation concepts, trustworthiness information only from trustworthy acquaintance peers can be used to obtain the ranking factor. The trustworthiness of an acquaintance peer shows how much a peer can trusts the acquaintance peer while the ranking factor of an acquaintance peer shows how much the acquaintance peer is trusted by other trustworthy acquaintance peers. Then, we evaluate the trustworthiness and ranking factor in presence of faulty peers.

Large companies increasingly look for collaborations with new ventures to accelerate their innovation process, and researchers stress the potential of such partnerships to develop innovations. But when are entrepreneurs willing to engage in a partnership with a larger player? We seek to understand when founders of new ventures are willing to engage in such asymmetric partnerships through consideration of the characteristics of the entrepreneurial decision maker and the perceived attributes of the larger counterpart. The results of a conjoint experiment with 115 startup entrepreneurs suggest that among the partner selection criteria a high level of openness on the part of the large corporate company and concise contractual design signal trustworthiness to entrepreneurs, which has a positive impact on their willingness to engage in collaborative innovation. Our study also suggests that entrepreneurs’ self-efficacy reduces the willingness to partner and the positive impact of concise contractual designs. The results have implications for the self-concept and design of innovation and partner management of large firms, and for entrepreneurs who consider asymmetric partnerships a growth opportunity.

Significant attempts have been made by national governments in recent years to provide services and information on the Internet using information and communication technology. However, the accomplishment of these efforts strongly depends on how the targeted users, such as citizens, relay, use and adopt them. As a consequence, a common need to understand the adoption and diffusion of electronic government, or e-government, has emerged in both developed and developing countries. Several impediments may prevent citizens from adopting e-government services, however, and trust is one of the major barriers. Therefore, this study aims to understand the influence of citizens' trust on the adoption of e-government services in the example of Saudi Arabia. From the data analysis, the exogenous variables of trust in Internet, government ability, government benevolence and integrity, and social influence were found to significantly affect citizens' trust in e-government services, whilst citizens' trust propensity was found to more usefully predict citizens' behavioural intention to use e-government services.

In order to evaluate and select the conceptual design solution better, the concept of trustworthiness is introduced, and proposes a conceptual design solution evaluation and selection algorithm based on trustworthiness. That is to get the comprehensive score by related trustworthiness computation, and then the preferable solution is ultimately selected. Finally, two experiments prove the necessity and feasibility of the algorithm, and it has a certain useful value.