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Given the lack of understanding of social marketing success in theory and practice, this study aims to investigate how social marketing experts conceptualize success.

In this qualitative study, the authors conducted an open-ended online questionnaire with 48 worldwide social marketing experts, most with more than 20 years of experience in the field. The authors analyzed data using topic modeling, a machine-learning method that groups responses/terms into cluster topics based on similarities. Keywords in each topic served to generate themes for discussion.

While behavior change is mentioned as paramount to conceptualizing success, participants prefer to use more tangible and less complex forms to define/measure success, such as campaign recall uptick. In addition, lack of funding was considered an important factor in measuring success. This study provides a two-stage taxonomy to better understand success in social marketing.

To the best of the authors’ knowledge, this study is one of the first to conceptualize success in social marketing practice.

Despite considerable research on the subject, there is still some misunderstanding about what characterizes successful project delivery in construction projects. Evaluating project delivery success is crucial for organizations since it enables them to prepare for future growth through more effective project management mechanisms and rank the organization's projects for continuous improvement. There is considerable disagreement over a set of success criteria that can be applied to all kinds of projects when evaluating project delivery success, making it a complicated procedure for practitioners and scholars. This research seeks to alleviate the problem by validating and testing a systematic project delivery success model (3D integration model) in the Australian construction industry. The aim is to establish a dependable approach built upon prior research and reliable in evaluating delivery success for any project type.

Based on a novel project delivery success model, this research applies a case study methodology to analyse 40 construction projects undertaken by a single Australian project management consultancy. The research utilizes a mixed-method research approach and triangulates three sets of data. First, the project delivery success (PDS) scores of the projects are calculated by the model. Second, a qualitative analysis targeting the performance of the same projects using a different system called the performance assessment review (PAR) scores was obtained. These culminate in two sets of ranking. The third step seeks validation of results from the head of the partnering organization that has undertaken the projects.

The findings of this study indicate that the 3D integration model is accurate and reliable in measuring the success of project delivery in construction projects of various sizes, locations and durations. While the model uses six key performance indicators (KPIs) to measure delivery success, it is evident that three of these may significantly improve the likelihood of PDS: value, speed and impact. Project managers should focus on these priority aspects of performance to generate better results.

Restrictions inherent to the case study approach are identified for this mixed-method multiple-case study research. There is a limitation on the sample size in this study. Despite the researcher's best efforts, no other firm was willing to share such essential data; therefore, only 40 case studies could be analysed. Nonetheless, the number of case studies met the literature's requirements for adequate units for multiple-case research. This research only looked at Australian construction projects. Thus, the conclusions may not seem applicable to other countries or industries. The authors investigated testing the PDS in the construction sector. It can assist in improving efficiency and resource optimization in this area. Nonetheless, the same technique may be used to analyse and rank the success of non-construction projects.

Despite the research conducted previously on the PDS of construction projects, there is still confusion among researchers and practitioners about what constitutes a successful project delivery. Although several studies have attempted to address this confusion, no consensus on consistent performance metrics or a practical project success model has been formed. More importantly, (1) the ability to measure success across multiple project types, (2) the use of triple bottom line (TBL) to incorporate sustainability in evaluating delivery success and (3) the use of a complexity measurement tool to adjust delivery success scores set the 3D integration model apart from others.

This research aims to develop and test a model for measuring end-user satisfaction (EUS) in a practical manner and then statistically verify its reliability and validity.

A comprehensive list of attributes using extensive literature review, focus group and brainstorming meetings were used to create a set of attributes for the model. These attributes were then used in a survey among the end-users (N = 687) of seven case studies with different characteristics (type, size and location) to assess the reliability and validity of the model. The statistical methods included reliability tests (Cronbach's alpha), confirmatory factor analysis (CFA) and correlation analysis), canonical discriminant analysis (CDA), item response theory (IRT) and model specification tests.

EUS must be quantified before determining a project's overall performance. The analysis of repeatability and consistency (reliability and validity) performed on case studies (data collected from the end-users) strongly suggests that the EUS model is robust for a range of project types.

Although many studies have proposed customer satisfaction models in the project success context, research on quantitative measurement tools is scarce. The paper departs from past research and develops and validates a new EUS model independent of project characteristics (while the study's limitations are acknowledged).

Despite the increasing role of the data warehouse as a supportive decision-making tool in today's business world, academic research for measuring its effectiveness has been lacking. This paucity of academic interest stimulated us to evaluate data warehousing effectiveness in the organizational context of Jordanian banks.

This paper develops a theoretical model specific to the data warehouse system domain that builds on the DeLone and McLean model. The model is empirically tested by means of structural equation modelling applying the partial least squares approach and using data collected in a survey questionnaire from 127 respondents at Jordanian banks.

Empirical data analysis supported that data quality, system quality, user satisfaction, individual benefits and organizational benefits have made strong contributions to data warehousing effectiveness in our organizational data context.

The results provide a better understanding of the data warehouse effectiveness and its importance in enabling the Jordanian banks to be competitive.

This study is indeed one of the first empirical attempts to measure data warehouse system effectiveness and the first of its kind in an emerging country such as Jordan.

Despite several research efforts tackling construction project risks globally, tertiary education building projects are not devoid of experiencing risks with cascading effects on projects. In the past decades, there has been increasing application of linear assessments of risks in construction risk management practices. However, this study aims to assess the influence of risk factors on the success of tertiary education building projects using a structural equation modelling approach. This study will further reinforce the risk factors that require attention because risk factors are not linear but interdependent.

A quantitative research method was undertaken in this study, where data collection was achieved via a structured questionnaire survey. In total, 452 questionnaires were administered to client representatives, consultants and contractors involved in executing tertiary education building projects across five public tertiary education institutions in Ondo State, Nigeria. Of 452 questionnaires, 279 were found usable for the analysis, implying a response rate of 61.73%. The Cronbach α test, average variances extracted and composite reliabilities values show high reliability and internal consistency of the instrument used for data gathering. Furthermore, the study adopted percentile, mean, correlation, regression analysis and structural equation modelling for analyzing the data collected upon which the study’s inferences were based.

The study found that three out of six criteria for measuring the success of tertiary education building projects were significantly affected by risk factors while using the structural equation modelling technique. With this non-linear method of assessment, completion to time was significantly impacted by environmental risk factors. In addition, safety performance was also significantly influenced by logistic, environmental and legal risk factors; furthermore, logistics, design and environmental risks significantly affected profit. However, completion to cost, standard/quality and end-user satisfaction was not significantly affected by the risk factors in tertiary education building projects.

The quantitative data used for the analysis are limited to the tertiary education building projects from selected five tertiary education institutions in Ondo State; therefore, the results do not indicate all tertiary institutions in Nigeria. In addition, the findings are based on building projects that were procured through a competitive tendering arrangement only and thus considered a limitation for this study.

Not all the risks significantly influence the tertiary education building projects. Therefore, risk factors with a significant effect on the success indicators of tertiary education building projects should be prioritized for a successful project. While risk factors have not affected the completion to cost per se, the study implies that the resultant effect of risks on other success indicators could have a cascading effect on these projects in terms of cost and time overruns. These results may assist during the project risk management while also addressing complexity and uncertainty to avoid chaos in a tertiary education building projects.

The study found significant construction risk factors impacting the success of tertiary education building projects using a non-linear methodology, an extension beyond the usual linear method of assessment of risk impacts on the project performance.

Failures in both followership and leadership become inevitable as mega construction projects are directed and controlled by toxic leaders. Consequently, team member's desire for knowledge hoarding silence is triggered and goal alignment between the leader and team members suddenly fades away to realize success in mega projects. Considering the growing importance of these rarely examined constructs and fragmented literature on toxic leadership (TL), team silence and mega project success (PS) in the global construction industry, the present study aimed to examine the effects of TL and project team member's silence (PTMS) on the success of mega construction projects. Moreover, the mediating influence of PTMS to link TL and mega construction PS has also been explored.

Drawing on survey data of 326 project professionals directly associated with mega construction projects worth US$62bn under the China–Pakistan Economic Corridor (CPEC), the conceptual model was tested with covariance-based structural equation modeling (CB-SEM) using Mplus program. Scales were adapted from previous research to measure TL (with its five-dimensions including abusive supervision, authoritarian leadership, self-promotion, narcissism and unpredictability), PS (with its three-dimensions including project management success, project ownership success and project investment success) and project team members' silence. Reflective–formative second order assessments were specifically applied to measure the multi-dimensional nature of TL and PS, respectively.

Mplus estimations revealed that TL negatively influences PS, besides forcing a culture of silence among project team members. Interestingly, the relationship between TL and PS is also negatively mediated by the PTMS.

The present study's findings are derived from data of project professionals (N = 326) to examine success in megaprojects under the CPEC. Hence, these findings may be re-validated through future studies on similar megaprojects (e.g. China's Belt and Road Initiative (BRI) worth US$8tn) that may also be predicated by TL tendencies, silent cultures and high-stakes involved to seize PS.

Policymakers, construction practitioners and other key stakeholders (e.g. departmental heads/supervisors) can take advantage of this new evidence to better interpret the success paradox in mega projects, and to reduce the spread and long-term damage of TL on team members and eventually create opportunities for PS.

The present study's novelty is manifested within this first empirical evidence on TL that breeds team silence in underperforming mega projects. Notably, present study offers alarming evidence on mega projects that can be easily derailed from success, as they continue to suffer from team silence and TL.

Digital Libraries are complex, and this complexity is a motive to study user success on the behalf of appropriate user success models. These models comprise the factors which play a part between people, technology and organizations. The purpose of this study was to specify and examine an integrated digital library user success (IDLUS) model within the context of digital library settings, Higher Education Commission National Digital Library (HEC-NDL) of Pakistan, by adopting and reusing the existing digital library and Web success models.

Stratified random sampling technique was used to choose the sample from the University of the Punjab, a highly ranked public sector university in Pakistan. Participants were asked to complete an adapted survey questionnaire. A total of 355 completed and usable questionnaires were obtained. Data analyses through confirmatory factor analyses and structural equation modeling produced the results that have supported the proposed IDLUS model. The proposed IDLUS model was tested and supported through model fit statistics in the academic computing environment of the HEC-NDL of Pakistan.

Findings revealed that relationships between the latent variables hypothesized in the model were confirmed.

The study has both theoretical and practical ramifications for academicians and information system designers and developers.

The IDLUS model is recommended first time in the history of librarianship in Pakistan as an overall user success model in the digital library information system computing environment. That made numerous recommendations for future research in the field of information management, particularly for digital library development at national and international levels.

A crucial question still remains unanswered as to whether data analytics-oriented business intelligence (hereafter, BI) technologies can bring organizational value and benefits. Thereby, several researchers called for further empirical research to extend the limited knowledge in this critical area. In an attempt to deal with this issue, we presented and tested a theoretical model to assess BI effectiveness at the organizational benefits level in this research article.

The suggested research model expands the application of the DeLone and McLean model in BI technology success or effectiveness research from individual level to organizational level. A cross-sectional survey is developed to obtain primary quantitative data from business and technology managers who are depending on BI technologies to make operational, technical and strategic decisions in Jordanian-listed firms.

Empirical findings show that system quality, information quality and training quality are significant predictors of user satisfaction, but not of perceived benefit. Data quality was found to be a strong predictor of both perceived benefit and user satisfaction. The influence of perceived benefit on user satisfaction was significant in turn both factors positively affect organizational benefits.

This research paper is a pioneering effort to assess BI technology effectiveness at an organizational level outside the context of developed countries. To the best of the authors’ knowledge, no prior research has combined all dimensions used in this research in one single model.

Despite being one of the most used dependent variables in expatriate management research, no clear-cut understanding exists of what expatriate success means. Thus, this study aims to propose an integrative definition of expatriate success by providing an overview of expatriate success's dimensions, antecedents, and their interplay.

A systematic literature review (SLR) was conducted to achieve the purpose. A total of 249 empirical studies (quantitative 111, qualitative 50, mixed-methods 17), literature reviews (67) and meta-analyses (4) on expatriate success were reviewed from Web of Science and Scopus databases published from 1990 until December 2021. The study selection criteria followed the PRISMA flowchart steps, and then descriptive and network analyses were performed to identify expatriates' success dimensions, antecedents and their interplay.

The findings show the interplay among antecedents and dimensions of expatriate success across three levels (individual, interpersonal and organisational) to clarify the concept of expatriate success. Also, the study offers a comprehensive definition of expatriate success based on the dimensions identified.

The suggested definition of expatriate success elucidates the “atheoretical”, multidimensional and socially constructed nature of the construct and hence, calls for more “theoretical”, multidimensional and subjective considerations of the term to ground human resource management practices addressed to attain expatriates' success.

This paper provides an integrative definition of expatriate success, giving greater insight into the construct, in addition to critically reflecting on it.

Process mining (PM) specialises in extracting insights from event logs to facilitate the improvement of an organisation's business processes. Industry trends show the proliferation and continued growth of PM techniques. To address the minimal attention given to developing empirically supported frameworks to assess the nature of impact in the PM domain, this study proposes a framework that identifies the key categories of PM impacts and their interrelationships.

The qualitatively derived framework is built, re-specified and validated from a diverse collection of 62 PM case reports. With multiple rounds of coding supported by coder corroborations, inductively extracted concepts relating to impact from a first set of 12 case reports were grouped into themes and sub-themes to derive an a-priori framework by adopting the balanced scorecard as a theoretical lens. Concepts from the remaining 50 case reports were deductively grouped to re-specify and validate the proposed PM impacts framework. Further analysis identified interrelationships between impacts, which extends our understanding of the identified PM impacts.

The proposed framework captures PM impacts in four main categories: (a) impact on the process, (b) customer impact, (c) financial impact, and (d) impact on innovation and learning. The authors extended this analysis to identify the interrelationships between these categories, which vividly demonstrates how impact on the process mediates the attainment of the other three impact types.

The need for a deeper understanding of PM impacts within the context of contemporary PM practice is addressed by this work. The PM impacts framework provides a classification of PM impacts into four categories with 19 subcategories. It also identifies direct, moderating and mediating relationships between categories and subcategories whilst highlighting the role of impact on the process as a precursor to the other types of PM impact.