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Scientific papers and patents are reliable sources of knowledge carriers for measuring science and technology advances, predicting technological trends, and formulating technology strategies. Although the idea of entirely using the two knowledge carriers is rapidly emerging in academic discussion, a theoretical framing of the comparisons is still not present in literature. This study conducts bibliometrics on 2986 patent families and 4755 scientific papers related to silicon carbide metal–oxide-semiconductor field-effect transistor (SiC-MOSFET) to identify its technological trends and compare the similarities and differences in knowledge generation and diffusion in science and technology. Our methodological framework consists of a combination of geographic distribution (identifying the research developments and distribution), cooperation networks (analyzing organisation collaboration and individual research cooperation), noun phrase co-occurrence clusters (discovering hot research topics), and the global main path analyses of citation networks (tracking the trajectory of knowledge flows). Ultimately, our results contribute to recent bibliometric paradigms beyond discovering the role of scientific papers and patents in promoting science and technology integration. [ABSTRACT FROM AUTHOR]

Chinese empirical legal research has undergone three stages of development, with the present stage being characterised by a proliferation of statistical and quantitative research following the inception of the online platform for judgment documents of the Supeme People's Court in 2014. Despite these advancements, empirical legal resem-ch based on judgment documents continues to grapple with a multitude of challenges and limitations. Three primary issues pervade the majority of such studies: (1) judgment documents themselves may not be reliable sources of legal materials; (2) the selection methods and research designs employed in empirical legal Tesearch may be overly simplistic or subjective, leading to biased or invalid results; and (3) there is a trade-of between accuracy and genemlisability. This article posits that empilical legal research ought to achieve the three progressively advancing functions of verification, falsification and innovation, striving to eradicate ambiguity in legislation and bolster legislative technology involving data and statistics. Furthermore, empirical legal research should be aware of its own limitations and avoid excessive extremism in its development. It is also important to consider the influence of advanced technology and maintain an open exploratory attitude towards other possible approaches. [ABSTRACT FROM AUTHOR]

A substantial number of social science studies have shown a lack of conceptual clarity, inadequate understanding of the nature of the empirical research approaches, and undue preference for deduction, which have caused much confusion, created paradigmatic incommensurability, and impeded scientific advancement. This study, through conceptual review and analysis of canonical discussions of concepts and the reasoning approaches of deduction and induction and their applications in social science theorization by philosophers and social scientists, is purported to unveil the logical nature of empirical research and examine the legitimacy of the preference of deduction among social scientists. The findings note that conceptual clarity as the foundation of social science research, exchange, and replication can be achieved through interdisciplinary stress of conceptual analyses to establish universal measurements and that the primacy of deduction in social sciences needs to concede to or be balanced with induction for new knowledge, more discoveries, and scientific advancement. The study recommends that institutions and researchers of social sciences invest more in conceptual analysis and inductive research through collaboration and separate efforts., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

We describe the pioneering role of the Production and Operations Management (POM) in promoting empirical research in innovation, operations, and supply chain management. We also review and discuss the most influential empirical papers published in POM based on each paper's Google Scholar citation counts. We selected the top 200 cited papers from the 2085 papers published or forthcoming in POM to identify the most influential empirical papers. We classify these 200 papers into three categories: (a) review and conceptual development, (b) analytical, and (c) empirical papers, and then compare these papers across the categories in terms of citation counts. Next we analyze the 75 empirical papers from the top 200 cited papers published in POM by covered topics, data sources, and data analysis methods. Focusing the analysis on empirical papers among the top 200 cited papers can underrepresent emerging themes among the more recently published empirical papers. Therefore, we also analyze 19 more recent empirical papers from 2016 to 2021 that are not covered in the top 200 cited papers but have been impactful given the brief time since their publication. We conclude by offering our thoughts on how editors, reviewers, and authors can work together to further enhance and ensure the quality and influence of future operations management (OM) empirical science research. [ABSTRACT FROM AUTHOR]

The International Conference on Cognitive Modeling brings together researchers from around the world whose main goal is to build computational systems that reflect the internal processes of the mind. In this issue, we present the five best representative papers on this work from our 19th meeting, ICCM 2021, which was held virtually from July 3 to July 9, 2021. Three of these papers provide new techniques for refining computational models, giving better methods for taking empirical data and producing accurate computational models of the cognitive systems that produce them. The other two papers focus on explanation: using models to elucidate the underlying processes affecting cognition in such diverse domains as logical reasoning and the effects of caffeine. [ABSTRACT FROM AUTHOR]

Reading scholarly articles is a core practice in academic seminars, which proceed under the assumption that seminar participants have read assigned texts and will incorporate the knowledge acquired from these texts into seminar discussions and train reading techniques. However, this seemingly self-evident situation perhaps only represents an ideal rather than actual seminar practices. This Science and Technology Studies-oriented contribution based on qualitative empirical research (participant observation, self-study, short interviews, forum theater experiments) will show how, where, when, and why students and lecturers do read texts, and what tactics they use when they have not read the texts 'properly,' 'fully,' or at all. How do they perform reading/not-reading; how does reading/not-reading bias knowledge circulation? In this hybrid process of collective and individual reading, reading and discussing seem to be intertwined, and texts become effective as actors, for example as digital scans or piles of paper. Reading and text-based discussions are material knowledge practices that entangle and are entangled in hegemonial arrangements. My aim is to make visible and negotiable an often self-evidently accomplished performativity of collective and individual reading, in its concrete and diverse practices, in order to work productively with the epistemological and didactic consequences. [ABSTRACT FROM AUTHOR]

With growing internationalism, there is a shift in research patterns in developing countries, especially China and India, generating vital and contemporary research areas that are beginning to challenge the existing Western‐dominated research literature in social sciences. Yet, many of the new ideas within conceptual papers by the social sciences are not empirically validated, let alone operationalized. This is where the group concept mapping method can play a role in bridging the gap between phenomenal conceptualization and having an empirically valid model that can then be operationalized. The group concept mapping process involves five steps: create statements, sort statements, run multidimensional scaling (MDS) of sorted units, run cluster analysis, and label the clusters. This approach allows for the collective thoughts of a pre‐defined group to be collected and organized into a tangible output with academic rigor. This paper offers an overview of the group concept mapping methodology, discussing the processes of the method, how the method can be utilized fully within the business and broader social science context, and the strengths, weaknesses, and practical implications of group concept mapping. [ABSTRACT FROM AUTHOR]

The literature of neuroimaging meta‐analysis has been thriving for over a decade. A majority of them were coordinate‐based meta‐analyses, particularly the activation likelihood estimation (ALE) approach. A meta‐evaluation of these meta‐analyses was performed to qualitatively evaluate their design and reporting standards. The publications listed from the BrainMap website were screened. Six hundred and three ALE papers published during 2010–2019 were included and analysed. For reporting standards, most of the ALE papers reported their total number of Papers involved and mentioned the inclusion/exclusion criteria on Paper selection. However, most papers did not describe how data redundancy was avoided when multiple related Experiments were reported within one paper. The most prevalent repeated‐measures correction methods were voxel‐level FDR (54.4%) and cluster‐level FWE (33.8%), with the latter quickly replacing the former since 2016. For study characteristics, sample size in terms of number of Papers included per ALE paper and number of Experiments per analysis seemed to be stable over the decade. One‐fifth of the surveyed ALE papers failed to meet the recommendation of having >17 Experiments per analysis. For data sharing, most of them did not provide input and output data. In conclusion, the field has matured well in terms of rising dominance of cluster‐level FWE correction, and slightly improved reporting on elimination of data redundancy and providing input data. The provision of Data and Code availability statements and flow chart of literature screening process, as well as data submission to BrainMap, should be more encouraged. [ABSTRACT FROM AUTHOR]

The article explores the use of theory in empirical papers presented at the ISIC: The Information Behavior Conference, from 1996 to 2020. The study examines the inclusion or lack of theory, the level of theory use, the specific theories used, and the disciplines from which these theories originated. The results indicate that most papers include theory, with many using theory substantially, but there is a significant decrease in theory use between the early and recent years of the conference.

The paper responds to the need for understanding trends and gaps in extant research related to adult education in mathematics and numeracy, given changing skill demands and skill gaps regarding adults, and related policy, theorizing, and practice trends. This paper presents the results of a scoping review of recent empirical research related to adult education in mathematics and numeracy, published in 22 selected journals from 2019 to 2022, including 15 journals in adult education and seven in mathematics education. The results show that only 39 relevant empirical studies were found among over 2300 research papers reviewed, and that few of those focus on practice-related of adult education in mathematics and numeracy. The results provide quantitative evidence suggesting that the field of adult numeracy education is under-researched, and help to identify gaps in empirical research involving adult numeracy, including on emerging topics such as on modeling and critical interpretation. The results also point to research opportunities that can strengthen theorizing and practice in both mathematics education and adult numeracy education. [ABSTRACT FROM AUTHOR]

Compared to previous studies that generally detect scientific breakthroughs based on citation patterns, this article proposes a knowledge entity‐based disruption indicator by quantifying the change of knowledge directly created and inspired by scientific breakthroughs to their evolutionary trajectories. Two groups of analytic units, including MeSH terms and their co‐occurrences, are employed independently by the indicator to measure the change of knowledge. The effectiveness of the proposed indicators was evaluated against the four datasets of scientific breakthroughs derived from four recognition trials. In terms of identifying scientific breakthroughs, the proposed disruption indicator based on MeSH co‐occurrences outperforms that based on MeSH terms and three earlier citation‐based disruption indicators. It is also shown that in our indicator, measuring the change of knowledge inspired by the focal paper in its evolutionary trajectory is a larger contributor than measuring the change created by the focal paper. Our study not only offers empirical insights into conceptual understanding of scientific breakthroughs but also provides practical disruption indicator for scientists and science management agencies searching for valuable research. [ABSTRACT FROM AUTHOR]

The world is accelerating globalization and urbanization; thus, planning plays an irreplaceable role in the macro development, especially in sustainable development. Planning research is important in turning theories of planning into urban practices. This research based on the theory that planning research is crucial, as it represents that planning-related activities improve processes in urbanization. However, the current understanding of the importance of planning research is limited. There is no research on the interaction between planning research and macro national development to support the importance of planning or its research. This study uses 750,000 articles on urban planning fields from WoS from 1950 to the present. Firstly, the study concludes the investment pattern changes of the global planning research. Over the past 70 years, the total number and diversity of countries engaged in planning research have grown rapidly, and developing countries have gradually integrated into the mainstream research community and become the main contributors. Secondly, the investment intensity and characteristics of planning research are consistent with the speed and characteristics of urbanization, which proves that to some extent, the demand of urbanization development drives the investment of planning research. Then, according to the different characteristics of planning research investment in different countries, this paper summarizes the main investment characteristics of major countries, analyzes the development rule behind the investment characteristics, and predicts the interaction with the international political and economic pattern. By analyzing the relationship between planning research intensity and urbanization, it is found that the investment intensity of planning research has a time rule with urbanization and has different interactions in different stages of urbanization development. It was found that the intensity of planning research was strongly correlated with HDI, and the amount of research was crucial. [ABSTRACT FROM AUTHOR]

Context: Software product lines (SPLs) have reached a considerable level of adoption in the software industry. The most commonly used models for managing the variability of SPLs are feature models (FMs). The analysis of FMs is an error-prone, tedious task, and it is not feasible to accomplish this task manually with large-scale FMs. In recent years, much effort has been devoted to developing reasoning algorithms for FMs. Aim: To synthesize the evidence on the use of reasoning algorithms for feature modeling. Method: We conducted a systematic mapping study, including six research questions. This study included 66 papers published from 2010 to 2020. Results: We found that most algorithms were used in the domain stage (70%). The most commonly used technologies were transformations (18%). As for the origins of the proposals, they were mainly rooted in academia (76%). The FODA model continued to be the most frequently used representation for feature modeling (70%). A large majority of the papers presented some empirical validation process (90%). Conclusion: We were able to respond to the RQs. The FODA model is consolidated as a reference within SPLs to manage variability. Responses to RQ2 and RQ6 require further review. [ABSTRACT FROM AUTHOR]

Despite artisanal and small-scale mining (ASM) being recognized in Ghana for decades as a legitimate livelihood source for rural folks, over 85% of ASM operations are carried out informally and outside state regulation due to limited understanding of the sector's complex local dynamics in policy and literature. This therefore presents various environmental challenges. This paper explores local perspectives on why miners continue to operate 'illegally' inspite of existing formalization efforts by the state. The study uses a qualitative exploratory design that includes case studies and semi-structured interviews in selected mining communities and core mining regulatory institutions in Ghana to collect primary and secondary data. The findings reveal a lack of understanding of the multifaceted nature of the sector's activities in policy on two interrelated fronts. First, there is little interconnection between formal policy efforts and pre-existing resource norms particularly regarding customary land systems. Second, findings further reveal a generic ASM formalization framework that fails to bring diverse forms of ASM operations under appropriate forms of control, undermining the capacity of some of the sector's operators to comply with formal regulations. It is recommended that policy makers use a more bottom-up approach to ASM formalization in order to gain adequate and accurate understanding of these local level dynamics in policy. [ABSTRACT FROM AUTHOR]

Co-opetition is gaining increasing attention as a potentially useful form of inter-organisational collaboration model to improve firms' sustainable performance. However, limited previous studies have provided a clear substantive theory or offered empirical evidence for the process of sustainability-driven co-opetition. This paper explores how competing companies can collaborate in their supply chains (SCs) to achieve a higher level of sustainability performance by identifying drivers, facilitators and barriers of co-opetition. Based on two explorative case studies of co-opetition in the UK, the findings of this paper lead to a number of propositions and a theoretical framework for sustainability-driven co-opetition in SCs. This study contributes to the literature by providing a more in-depth understanding of co-opetition as a strategic capability for firms. This paper also proves the feasibility of a combined use of Resource-Based View and Network Theory perspectives in explaining a paradoxical inter-organisational relationship like co-opetition. A road map for sustainability-driven co-opetition in SCs is also provided as a heuristic decision model for practitioners. [ABSTRACT FROM AUTHOR]

Managerial shared leadership is a practice that goes beyond traditional ways of organising leadership functions. It is an organisational phenomenon where a few individuals share responsibility for the tasks of a managerial position. This paper reviews 67 empirical papers published in scientific journals. The review covers 55 years (1965–2019). The aim is to contribute knowledge about managerial shared leadership as a research field and offer some relevant theoretical concepts. No review to date has specifically focused on managerial shared leadership, and this paper intends to close this knowledge gap. The paper details the start of managerial shared leadership as a research field, presents a bibliometric analysis and the methodological approaches used, and describes the structural characteristics of managerial shared leadership. The paper includes a thematic content analysis of necessary and enabling antecedents and outcomes. Historically, the imprecise use of concepts has hampered managerial shared leadership's development into a cohesive research field, so this paper develops and uses theoretical concepts to form a theoretical construct for the entire field. This construct is briefly discussed in relation to general shared leadership theory and critical leadership studies. In practice, managerial shared leadership may provide leadership solutions where there is an imbalance between demands and resources while managing complex situations. [ABSTRACT FROM AUTHOR]

Research on positive affect (PA) and negative affect (NA) is often guided by the rotational variant of the circumplex model of affect (RCMA). According to the RCMA, PA and NA are posited to be orthogonal, with PA ranging from the union of positive valence and high activation (e.g., excited) to the union of negative valence and low activation (e.g., sluggish), and NA ranging from the union of negative valence and high activation (e.g., distressed) to the union of positive valence and low activation (e.g., relaxed). However, many authors incorrectly interpret the RCMA as positing that positively valenced affect (i.e., pleasure) and negatively valenced affect (i.e., displeasure)--rather than PA and NA, as defined in the RCMA--are orthogonal. This "received view" of the RCMA has led to significant confusion in the literature. The present paper articulates the "received view" of the RCMA and characterizes its prevalence in psychological research. A random sample of 140 empirical research articles on affect published in 14 high-impact journals covering a range of psychological subdisciplines were reviewed. Over half of the articles subscribing to the RCMA showed evidence of the "received view," demonstrating that misuse of the terms PA and NA in the context of the RCMA is rampant in the psychological literature. To reduce continued confusion in the literature, we recommend abandoning use of the terms positive affect and negative affect. We further recommend referring to the two dimensions of the RCMA as positive activation and negative activation, and the two poles of the valence dimension as positive valence and negative valence (or pleasure and displeasure). [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editors of the journal discuss the transparency of empirical research published in the journal in general and the papers published in this edition.

China is facing a serious land resource mismatch problem, which will profoundly affect the acceleration of economic growth and technological innovation. Reform of the industrial land allocation system can solve the mismatch of land resources, and that also has an important impact on the promotion of economic and technological development. This paper selects the data of Chinese A-share listed companies in Shanghai and Shenzhen from 2007 to 2020 as the research sample, constructs a double machine learning model, and empirically investigates the impact of a new industrial land use policy on firms' green innovation behavior. The study shows that: (1) the new industrial land use policy significantly promotes firms' substantive and strategic green technological innovation, and the effect on substantive green technological innovation is greater than that on strategic green technological innovation. (2) The enhancement of R&D investment sustainability and the "talent pool" effect are important mechanisms through which the new industrial land use policy influences firms' substantive and strategic green technological innovation. Meanwhile, the new industrial land use policy is conducive to firms' green coinnovation. (3) There is heterogeneity in the effect of the new industrial land use policy, which can significantly promote green technological innovation of firms in the eastern region, while it does not play a significant role in the green innovation behavior of firms in the central and western regions. The above research results enrich the research in the field of industrial land and innovation, help to understand more comprehensively the mechanism of new industrial land affecting firms' green technological innovation, and provide policy insights for strengthening the application of industrial land allocation reform in firms' green innovation. [ABSTRACT FROM AUTHOR]

This paper uses inter-provincial panel data from 2011 to 2017, a linear regression model, and a threshold model to conduct empirical analyses of the impact of the digital economy on China’s overall economic growth and the three main sectors of industry. The paper then investigates the impact and effects the digital economy has had on the economic growth of the three main sectors of industry in China’s eastern, central, and western regions. Finally, the paper investigates the most significant differences among the various regions and the threshold effects of urbanization levels on the relationship between the digital economy and economic growth. The findings indicate a significantly positive correlation between the digital economy and regional economic growth. Moreover, geographical factors notably influence this correlation. The digital economy exerts a positive effect on all sectors of industry. It may not substantially impact industrial development in regions with highly developed infrastructure. Regarding the other regions, the digital economy exhibits varying degrees of impact due to the differences in the specific indicators. The conclusion drawn by the threshold model is that the magnitude of the threshold effect correlates with geographic factors. No threshold effect was observed in the eastern region, while the threshold effect occurred in the central region when the urbanization levels for the provinces were below 0.6645. Similarly, the threshold effect was noted in the western region when the urbanization level was below 0.3931. Considering all of this, the study also offers policy recommendations that will help balance the regional development of digital economies, accelerate the digital transformation of traditional industries, enhance digital infrastructure construction, refine the formulation and implementation of data policy, and establish relevant incentive mechanisms. [ABSTRACT FROM AUTHOR]

Over the last few years, business simulation games (BSGs) in higher education have attracted attention. BSGs tend to actively engage students with course material, promoting higher engagement and motivation and enabling learning outcomes. Increasingly, researchers are trying to explore the full potential of these games with an upsurge of research in the BSG field in recent years. There is a need to understand the current state of research and future research opportunities; however, there is a lack of recent systematic literature reviews in BSG literature. This study addresses this gap by systematically compiling online empirical research from January 2015 to April 2022. We followed PRISMA guidelines to identify fifty-seven (57) papers reporting empirical evidence of the effectiveness of BSGs in teaching and learning. Findings showed that BSGs improve learning outcomes such as knowledge acquisition, cognitive and interactive skills, and behaviour. The review also summarises different issues concerning the integration of BSGs into the curriculum, learning theories used in the selected studies, and assessment methods used to evaluate student achievement in learning outcomes. The findings of this review summarise the current research activities and indicate existing deficiencies and potential research directions that can be used as the basis for future research into the use of BSGs in higher education. [ABSTRACT FROM AUTHOR]

Usable privacy and security researchers have developed a variety of approaches to represent risk to research participants. To understand how these approaches are used and when each might be most appropriate, we conducted a systematic literature review of methods used in security and privacy studies with human participants. From a sample of 633 papers published at five top conferences between 2014 and 2018 that included keywords related to both security/privacy and usability, we systematically selected and analyzed 284 fulllength papers that included human subjects studies. Our analysis focused on study methods; risk representation; the use of prototypes, scenarios, and educational intervention; the use of deception to simulate risk; and types of participants. We discuss benefits and shortcomings of the methods, and identify key methodological, ethical, and research challenges when representing and assessing security and privacy risk. We also provide guidelines for the reporting of user studies in security and privacy. [ABSTRACT FROM AUTHOR]

Public–Private Partnerships have been implemented globally as a key procurement strategy for addressing the issue of funding gaps amidst the immense pressure to deliver new major infrastructure projects. However, in current practice, procurement selection is applied to the entire bundle of project activities. This often leads to unduly large bundles of externalized project activities that create unduly large PPP contracts and attempt to transfer too much risk. To address this gap, this paper presents the development and testing of an implementable model that embodies a range of microeconomic theories—namely, transaction cost and resource-based theories—and property rights theory. This paper presents the first empirical testing of this model based on two road and two health projects, using competition as an independent measure of the validity of the recommended procurement strategy. The results provide compelling evidence that a rigorous application of the model will enable a substantial improvement of existing procurement approaches, such as identifying the most suitable bundle to be procured using a PPP approach. [ABSTRACT FROM AUTHOR]

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Formal theory and empirical research are complementary in building and advancing the body of knowledge in accounting in order to understand real‐world phenomena. We offer thoughts on opportunities for empiricists and theorists to collaborate, build on each other's work, and iterate over models and data to make progress. For empiricists, we see room for more descriptive work, more experimental work on testing formal theories, and more work on quantifying theoretical parameters. For theorists, we see room for theories explicitly tied to descriptive evidence, new theories on individuals' decision making in a data‐rich world, theories focused on accounting institutions and measurement issues, and richer theories for guiding empirical work and providing practical insights. We also encourage explicitly combining formal theory and empirical models by having both in one paper and by structural estimation. [ABSTRACT FROM AUTHOR]

Digital health technologies (DHTs) at the intersection of health, medical informatics, and business aim to enhance patient care through personalised digital approaches. Ensuring the efficacy and reliability of these innovations demands rigorous clinical validation. A PubMed literature review (January 2006 to July 2023) identified 1250 papers, highlighting growing academic interest. A focused narrative review (January 2018 to July 2023) delved into challenges, highlighting issues such as diverse regulatory landscapes, adoption issues in complex healthcare systems, and a plethora of evaluation frameworks lacking pragmatic guidance. Existing frameworks often omit crucial criteria, neglect empirical evidence, and clinical effectiveness is rarely included as a criterion for DHT quality. The paper underscores the urgency of addressing challenges in accreditation, adoption, business models, and integration to safeguard the quality, efficacy, and safety of DHTs. A pivotal illustration of collaborative efforts to address these challenges is exemplified by the Digital Health Validation Center, dedicated to generating clinical evidence of innovative healthcare technologies and facilitating seamless technology transfer. In conclusion, it is necessary to harmonise evaluation approaches and frameworks, improve regulatory clarity, and commit to collaboration to integrate rigorous clinical validation and empirical evidence throughout the DHT life cycle. [ABSTRACT FROM AUTHOR]

This paper examines the impact of the Belt and Road Initiative (BRI) on China's political influence in international affairs, as mediated by Chinese economic integration with the BRI countries. We propose that the BRI plays a role in influencing partner countries to support China's presence in the international community, and the economic integration of the BRI positively mediates the willingness of partner countries to align with China in international affairs. This paper uses panel data from 147 BRI countries collected between 2009 and 2020, and the difference-in-differences method, to estimate the political influence of the BRI. The results suggest that the BRI motivates partner countries to support the growth of China's influence in international affairs. The results of the causal mechanism analysis indicate that a significant and positive association between the implementation of the BRI and China's influence is mediated by promoting Chinese contracts, trade overseas, and outward FDI. The examinations of heterogeneity demonstrate that BRI countries that are developing, non-landlocked, non-neighboring, having signed the memorandum of understanding or cooperation memorandum of understanding, or lacking a Chinese investment guide are more likely to support China's political presence. This paper concludes with insights into how China implements the BRI to enhance its political ascent in the global order by facilitating economic integration of the BRI. [ABSTRACT FROM AUTHOR]

Many theoretical methods have been applied to research user behaviour and requirements. However, the uncertainty associated with customer characteristics often biases the conclusions drawn from customer research and affects the effectiveness of product design. In this paper, Bayesian networks (BN) are introduced into the research on customer behaviour analysis based upon theory of planned behaviour (TPB), and an analysis model driven by customer research data is established from the perspective of user behaviour intention to guide design optimisation. Combining the User background Factor with the TPB Factor, the model analyses the uncertainty of the association between the two, and corrects the errors in the designer's prior knowledge through structural learning. By a case study the paper finds that the evaluations that enhance customers' subjective norms and perceived behavioural control lead to a greater probability of purchase or use. In addition, customers with specific characteristics are more inclined to generate behaviour intention. The paper finally provides a design optimisation plan based upon the result of the research and discusses about the advantages of the research approaches and the directions of future researches. [ABSTRACT FROM AUTHOR]