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The purpose of this paper was to realize a non-destructive examination for printed circuit boards (PCBs) and to obtain an accurate and high-efficient image.

This paper provides an approach to realize a non-destructive examination for PCBs and to obtain an accurate and high-efficient image.

The result showed that cone-beam computed tomography (CT) image PCB detection based on an interactive cutting method had accuracy and high efficiency and can meet the non-destructive requirement of detection.

The result showed that cone-beam CT image PCB detection based on an interactive cutting method had accuracy and high efficiency and can meet the non-destructive requirement of detection.

This study identifies a new type of advertising, sponsored ad forwarding, in microblog contexts. It tests the effectiveness of designs of a message with an ad with regard to receivers who are purely online friends or offline friends.

In the main experiment, a three-by-two experimental design was employed. By random assignment, message senders forwarded an ad with either an other-oriented or a self-oriented message to a group of offline friends or purely online friends. In the control group, there was no message accompanying the ad. The data of 218 effective sender-receiver dyads were collected and compared.

The results show that a message with an other-oriented appeal is more effective than one with a self-oriented appeal for dyads with an offline relationship, and a message with a self-oriented appeal is more effective than one with an other-oriented appeal for dyads with a purely online relationship. Overall, the use of appeals significantly boosts ad effectiveness.

This study identifies a new type of marketing practice in social media, namely sponsored ad forwarding. It also proposes appeal orientation as a novel type of message content design. It shows how to apply the right appeal orientation to the right receiver groups, that is, offline or purely online friends.

This study aims to solve the problems of large training sample size, low data sample quality, low efficiency of the currently used classical model, high computational complexity of the existing concern mechanism, and high graphics processing unit (GPU) occupancy in the current visualization software defect prediction, proposing a method for software defect prediction termed recurrent criss-cross attention for weighted activation functions of recurrent SE-ResNet (RCCA-WRSR). First, following code visualization, the activation functions of the SE-ResNet model are replaced with a weighted combination of Relu and Elu to enhance model convergence. Additionally, an SE module is added before it to filter feature information, eliminating low-weight features to generate an improved residual network model, WRSR. To focus more on contextual information and establish connections between a pixel and those not in the same cross-path, the visualized red as integer, green as integer, blue as integer images are inputted into a model incorporating a fused RCCA module for defect prediction.

Software defect prediction based on code visualization is a new software defect prediction technology, which mainly realizes the defect prediction of code by visualizing code as image, and then applying attention mechanism to extract the features of image. However, the challenges of current visualization software defect prediction mainly include the large training sample size and low sample quality of the data, and the classical models used today are not efficient, and the existing attention mechanisms have high computational complexity and high GPU occupancy.

Experimental evaluation using ten open-source Java data sets from PROMISE and five existing methods demonstrates that the proposed approach achieves an F-measure value of 0.637 in predicting 16 cross-version projects, representing a 6.1% improvement.

RCCA-WRSR is a new visual software defect prediction based on recurrent criss-cross attention and improved residual network. This method effectively enhances the performance of software defect prediction.

By introducing Stacking algorithm to solve the underfitting problem caused by insufficient data in traditional machine learning, this paper provides a new solution to the cold start problem of entrepreneurial borrowing risk control.

The authors introduce semi-supervised learning and integrated learning into the field of migration learning, and innovatively propose the Stacking model migration learning, which can independently train models on entrepreneurial borrowing credit data, and then use the migration strategy itself as the learning object, and use the Stacking algorithm to combine the prediction results of the source domain model and the target domain model.

The effectiveness of the two migration learning models is evaluated with real data from an entrepreneurial borrowing. The algorithmic performance of the Stacking-based model migration learning is further improved compared to the benchmark model without migration learning techniques, with the model area under curve value rising to 0.8. Comparing the two migration learning models reveals that the model-based migration learning approach performs better. The reason for this is that the sample-based migration learning approach only eliminates the noisy samples that are relatively less similar to the entrepreneurial borrowing data. However, the calculation of similarity and the weighing of similarity are subjective, and there is no unified judgment standard and operation method, so there is no guarantee that the retained traditional credit samples have the same sample distribution and feature structure as the entrepreneurial borrowing data.

From a practical standpoint, on the one hand, it provides a new solution to the cold start problem of entrepreneurial borrowing risk control. The small number of labeled high-quality samples cannot support the learning and deployment of big data risk control models, which is the cold start problem of the entrepreneurial borrowing risk control system. By extending the training sample set with auxiliary domain data through suitable migration learning methods, the prediction performance of the model can be improved to a certain extent and more generalized laws can be learned.

This paper introduces the thought method of migration learning to the entrepreneurial borrowing scenario, provides a new solution to the cold start problem of the entrepreneurial borrowing risk control system and verifies the feasibility and effectiveness of the migration learning method applied in the risk control field through empirical data.

The purpose of this paper is to evaluate doctoral candidates’ innovative ability tendency.

This study uses the theory of gray target contribution to analyze the influence degree of doctoral candidates’ individual personality factor toward their innovative ability and calculate gray impact quantitative values.

Based on the theory of contribution degree of gray target, a nine-factor model of innovative personality of doctoral candidates is built. IP=f (B, H, G, Q1, Q2, A, I, F, O), (therein: B – intelligence, H – social boldness, G – perseverance, Q1 – experimental, Q2 – independence, A – gregariousness, I – sensibility, F – excitability, O – anxiety).

This study based on gray target contribution theory builds nine-factor doctoral candidates’ innovative personality model to test the innovative ability tendency of doctoral candidates, which makes cultivating units, mentors and doctoral candidates to know their innovative ability tendency well, perfecting their own knowledge structure in time, effectively improving their innovative ability. The system can also be applied to the work of doctoral candidates as a reference tool to evaluate the innovative ability of applicants.

This study quantitatively evaluates the influence of doctoral candidates’ personality index on the tendency of doctoral candidates’ innovative ability.

Extant research on supply chain integration defines integration in different ways, and mainly discusses a limited number of integration elements. The purpose of this paper is to develop a conceptual integration model which consists of comprehensive elements that are important to academic research and industrial practices.

Key literature survey with drawing threads of existing practices together for developing a systematic referential model and then verify the model with a real case.

Developed a model consisting of integration elements residing at the strategic, managerial, operational, and fundamental levels (bottom line). Based on the benefit alignment, the total integration requires supply chain partners to integrate resource flows (material, information, knowledge, and finance), processes and organization, planning and control activities and strategy.

The research is based on secondary data and a case study illustration. Further empirical research is required.

The normative model can guide managers to integrate resources and activities in their efforts for an effective supply chain management. It supplements the Supply Chain Operations Reference Model developed by the Supply Chain Council with an interface description, which may guide the development of information systems for supply chain integration.

The comprehensive model provides a more inclusive and integrated perspective of supply chain integration. It is expected that the consensus of supply chain integration could be achievable based on this model. The conceptual framework will assist the researchers to determine integration variables of supply chain.

The purpose of this study is to explore the categories of leader traits, their generation and their relationships in leaders’ socialization.

The authors take the case study method, which is the most suitable method to answer research questions on why and how to fulfill the study purpose on the basis of the case of Ruimin Zhang.

Leader traits are classified into four categories with respect to socialization, namely, root trait, driving trait, thinking trait and affair trait. The root trait and the driving trait form from the leader’s insight with the impact of key events, mutually promote and consolidate each other, and together derive the thinking trait and the affair trait on the basis of critical events, culture, family, education, etc. The thinking trait is the premise of the affair trait to be expressed in leadership behavior. The root trait and the driving trait together determine a leader’s growth direction and efficiency and can distinguish leaders from non-leaders. The thinking trait and the affair trait together determine the pattern and effectiveness of leadership behavior and can distinguish effective leadership from ineffective leadership.

This study transcends prior integral leader trait research by categorizing leader traits from the socialization perspective, makes a clear delineation on the interrelationships among categories of leader traits, analyzes their holistic functions on the leaders, reveals the formation and relationship mechanism of leader traits and identifies the types of leader traits that can work as the standards for distinguishing effective leaders from ineffective leaders or non-leaders.

This study promotes the development of the leader trait theory in the classification, formations, relationships and overall effect of leader traits.

Most studies in information behaviour have focussed on information behaviour aspects such as environmental uncertainty, scanning behaviour of top management executives, student and women information behaviour, information source and credibility, while little is known about the information behaviour of small- and medium-sized enterprises (SMEs) when the need for emerging information and communication technology (EICT) adoption decision-making arises. This paper, therefore, aims to explore the major determinants of perceived information need for EICT adoption by UK small service-oriented businesses.

The study adopted qualitative method to explore 13 key determinants of SME managers’ information behaviour for EICT adoption decision-making by using both unstructured and semi-structured interviews at two different stages with 20 participants drawn purposeful from Luton directories.

The study developed an extended technology, organisation and environment (TOE) framework by identifying and incorporating the information context which helped to unveil 13 key determinants of perceived information need and their impact on EICT adoption decision-making in SMEs. This further provided insight into understanding SMEs’ information behaviour. While the determinants associated with TOE and information contexts influence SMEs’ perceived information need for EICT adoption, the extent at which these four constructs shape SMEs’ perceived information need for EICT adoption decision-making differs.

The limitation of this study emerged because of the use of qualitative methodologies in relation to the research design, rigour in the collection and management of the large volume of the raw data, the data analysis and the credibility of the findings. This may lead to unforeseen respondent – and research – bias in the data analysis, which may lead to limited understanding of alternatives and insights into the key determinants of perceived information need for EICT adoption decision. Hence, other measures and approaches such as case study and mix-method could be deployed to further validate the findings. Also, one of the limitations of qualitative study has been the issue of theoretical generalizability of the framework. The generalizability of the formwork needs to be established across a wider range of population. Future studies may apply a confirmatory statistical techniques to test and ascertain the validity and reliability of the framework across a wider population. Such studies may be used as a benchmark for the theoretical constructs and the factors that may lead to success or failure of mobile marketing technology adoption.

The study has further enriched TOE framework and provided an analytical dimension for exploring key determinants of SMEs’ perceived information need for EICT adoption decision-making. It also demonstrates the capacity to provide a reliable explanation of the determinants and serves as a tool for evaluating the benefits or challenges of SMEs’ information behaviours when the need for EICT adoption arises.

While a substantial number of studies have examined information behaviour, most centred on choice of information source, student information behaviour, information behaviour of women, environmental uncertainty and scanning behaviour of top-level hotel executives. However, little is known about how the small and medium enterprise (SME) managers scan, seek, gather, document and use information relevant for emerging information and communication technology (EICT) adoption decision-making. This paper aims to examine the key success factors influencing SME manager’s information behaviour on EICT adoption decision-making.

This study deploys a qualitative approach to exploring 16 key success factors shaping SME managers’ information behaviour on EICT adoption decision-making. More specifically, the study adopted both unstructured and semi-structured interviews with 20 small business managers drawn purposeful from Crunch Database.

This study develops an extended technology, organisation and environment framework by incorporating the information context which helped to unravel 16 key success factors influencing small business managers’ information behaviour on EICT. From the technology context, uncertainty driven, compatibility, replacement of legacy technology, relative advantages, lack of technical know-how and perceived affordability fit for purpose influence SME managers’ information behaviour. Users’ acceptance information, efficiency driven, owner’s support shape the organisation context of perceived information need; competitor’s intelligence gathering, customer’s information gathering provider credibility and government policy influence the environmental context of perceived information need; and finally, perceived information sources credibility, herding event, testimonial and openness to other people’s ideas and experiences are shaped by the information context.

Qualitative research is normally subjective, interpretive and limited on the sample used. Because of the limited number of interviews, the generalisation of the framework and the finding is difficult. Therefore, the finding and the framework need to be established across broader population. The findings are vital considering the fact that small business managers are limited in knowledge and the study may improve the way and manner they go about seeking and gathering information relevant in adopting new ICT.

This research provides further insight into SME managers’ information behaviour by developing a framework and identifying main factors influencing SMEs information behaviours on EICT. Therefore, understanding such factors will enrich their knowledge on some of the factors that may shape their decisions during EICT adoption decision to make effective decision.

Prior studies mostly investigate initial shopping intention in developed countries. The purpose of this paper is to sketch and determine the impact of perceived usefulness (PU), perceived ease of use (PEOU), perceived value (PV), trust (TRT), perceived risk (PR), privacy concern (PC), internet literacy (IL), satisfaction (SAT) on online repatronage intention (ORI) among Malaysian experienced online shoppers.

A total of 219 valid questionnaires were collected via an online survey among experienced online shoppers across young and old students aged 18-31. Subsequently, the two-step structural equation modelling (SEM) technique was employed to empirically examine the proposed integrative theoretical research framework and model fit with maximum likelihood estimation.

The statistical analyses support the relationships between PU, PV, TRT and SAT with ORI while the relationships between PEOU, PR, PC and IL with ORI were rejected in which all the factors affecting ORI occur similarly across the study sample. The behaviour of experienced online shoppers was found to be different from findings of previous literature that examined initial adoption and intention. Due to the lack of distinction in the literature concerning experienced and inexperienced shoppers, our results show inconsistencies with prior research in examining ORI.

The paper suggests that future research consider multicultural analysis, atmosphere design, developing internet methodology and the role of flow experience in determining ORI. The research limitations and implications are also discussed.

By realizing the differences between inexperienced shoppers and experienced shoppers, online retailers should segment these groups more effectively and should implement a different marketing strategy to target the right segment, right shoppers along with the right marketing tactic. The antecedents of future intention of online shopping are influenced by various variables because the human behaviour is sophisticated in nature. Thus, academicians and practitioners should realize the implications of examining their target population/market based on an assessment of different antecedents.

This study is among the few attempts to examine attitudes and behaviour of Malaysian experienced online shoppers who have formed relevant experiences and skills in online shopping. Additionally, the paper empirically examine and distinct user perception of online retail attributes (including PU, PEOU, PV and PR), pre-purchase user attitudes (including TRT, PC, IL) and post-purchase users attitudes (including SAT) in forming ORI simultaneously.