1,720,965 research outputs found
Review of Dynamic Structural Equation Models for Real-Time Consumer Behaviour: Methodological Advances and Applications Insights
Full text linkThis study evaluated the transformative importance of dynamic SEM in offering a more thorough understanding of real-time consumer behaviours and thus transcending the limitations of traditional SEM approaches that typically rely on static data. The study analysed the recent advancements in the dynamic SEM and its capability to strengthen marketing strategies by accurately capturing evolving consumer interactions. The study evaluated the published peer-reviewed literature ranging from 2010 to 2024 to assess the advancement, comparisons, applications, accuracy and methodological complexities of both dynamic and traditional SEM approaches in the domain of consumer behaviours and interactions marketing analytics. The inclusion criteria were studies focusing on consumer behaviour, research articles published within 14 years, studies employing dynamic SEM methods and datasets that include time-series data. The findings for objective one show that dynamic SEM analyses complex, temporal and real-time data because it has been integrated with advanced modern methods and approaches such as Ecological Momentary Assessment and Experience Sampling Method, Bayesian methods for estimation, machine learning algorithms and cloud computing platforms. The findings for objective two indicate that dynamic SEM is practically and accurately capable of analysing temporal and real-time high-frequency, complex, and large-scale datasets from digital platforms like social media and e-commerce. The results obtained from the comparative analysis for objective three show that dynamic SEM provides significant improvements by offering a more accurate reflection of evolving consumer interactions and preferences than traditional SEM. Dynamic SEM integrates temporal elements and therefore allows for adeptly modelling consumer choices, moods, attitudes, and emotional states over time. Performance metrics such as MAE, RMS, and CFI confirm that dynamic SEM enhances fit and predictive precision. The findings show that dynamic SEM substantially and significantly outperforms traditional SEM since it has been integrated with advanced methods that enhance the understanding of real-time consumer behaviour and interactions by effectively capturing temporal variations in consumer behaviour and interactions. Thus, organisations should adopt and implement the dynamic SEM to optimise and improve their marketing strategies. The study contributes to knowledge that the dynamic SEM is superior in capturing real-time consumer behaviours, which results in enhancing marketing analytics and strategies
The influence of entrepreneurship education on entrepreneurial intentions: Perception of higher business education graduates
Full text linkThe purpose of this study was to explore the antecedents of entrepreneurial intentions among the Tanzanian Higher Business Education Graduates (HBE). The motivation for the study was because, despite the integration of entrepreneurship education (EE) in every degree programme, still many graduates had been unemployed. This cross-sectional study is based on primary data. An in-depth interview was conducted with a sample of 21 HBE graduates from various HBE institutions. Primary data collection was done using in-depth interview guide questions physically done by the researcher. Snowball and purposive sampling approaches were employed to identify respondents for this study. Content analysis method with the aid of NVivo version 11 software package was used to analyse the qualitative data. The study identifies five important antecedents of entrepreneurial intentions, namely, interpersonal traits, EE through competency-based training, planning and focus, successful groups which are close to a prospective entrepreneur, and government support. The findings task entrepreneurship educators, role models, close groups, professional supporters, and the government to concurrently foster the combinations of EE and other factors which were revealed to have the highest predictive power on entrepreneurial intention in the process of nurturing and psychologically developing the students’ entrepreneurial careers of self-reliance and self-employment. This research is novel and contributes to the body of knowledge in the existing antecedents of entrepreneurial intentions: given the emphasis on residual and new antecedents of entrepreneurial intentions essential for promoting the start-ups by the HBE graduates and enabling them to employ themselves
Factors Influencing Business Succession Planning among SMEs in Tanzania
Full text linkThe study intended to investigate factors influencing business succession planning among Small and Medium Enterprises (SMEs). It assessed how demographic characteristics, business size, and family related factors influence business succession planning. The research methodology involved surveying 25 SMEs and among 104 interviewed owners/supervisors, only a sample of 88 was analyzed by Chi-square to establish the relationship between independent and dependent variables. The findings show that the higher the age of SMEs owners, the higher the possibility of preparing the business successors. Also, males are associated with more chance of being involved in business succession planning, the sons having a big chance of being the successors. Furthermore, increase in the level of education of SMEs owners has a positive influence in preparing the successors. Similarly, business size has a positive influence on business succession planning, the bigger business being given the first priority. In contrary, increase in involvement of family members in SMEs has no influence on business succession planning. Lastly, increase in communication among family members has a positive influence on business succession planning. The study concludes that SMEs owners don’t prepare the business successors while still energetic. It further concludes that gender has an effect on business succession planning and that the owners who have low level of education die with their businesses because they rarely prepare the successors. The study recommends that the owners of SMEs should prepare the right business successors in time to make their businesses remain sustainably. Key words: Business succession planning, demographic characteristics, SME
Cultivating Future Graduate Entrepreneurs: A Holistic Exploration of Vital Entrepreneurial Skills from a Tripod-Based View and Evidence
Full text linkPurpose- This study aimed to examine essential entrepreneurial skills as perceived by students, practicing entrepreneurs, and employers in Tanzania, focusing on the ecosystems of Dar es Salaam and Mwanza.Design/Methodology- A qualitative cross-sectional design was employed, using stratified random sampling and purposive sampling to conduct in-depth interviews with students, entrepreneurs, and employers. Thematic analysis was used to interpret the qualitative data.Findings- The study identified ten critical entrepreneurial competencies: communication, problem-solving, adaptability, resilience, teamwork, creativity, initiative, networking, leadership, and customer focus. There was consensus among all groups regarding the importance of these skills, with students emphasizing curricula that incorporate real-world challenges, and entrepreneurs and employers stressing the need for practical experience, financial literacy, strategic thinking, innovation, and ethical decision-making.Practical Implications- The study offers recommendations for enhancing entrepreneurial education by integrating hands-on learning, internships, case studies, mentorship, and practical experience into academic programs. It also suggests a unified framework for curriculum enhancement, incorporating the perspectives of students, entrepreneurs, and employers to improve entrepreneurial education
Management succession planning and family-owned manufacturing businesses survival: The moderating role of firm’s background variables
Full text linkIt remains unclear how lack of management succession planning relates to the collapse of 87% of the Tanzanian family-owned manufacturing businesses (FOMBs) after the first generation. Also, the question of whether a firm’s background variables, namely; executive’s education level, business age, and business size, moderate the relationship between management succession planning and the survival of FOMBs remains unanswered. Therefore, this study investigated the relationship between succession planning and the survival of FOMBs, moderated by the firm’s background variables through the lens of resource-based theory as well as agency theory. A sample of 339 executives was randomly drawn from the FOMBs in Dar es Salaam city where the collapse of FOMBs after the first generation was revealed to be significant and surveyed using a structured questionnaire. Multiple linear regression was used as a quantitative data analysis technique with the support of SPSS as an analytical tool. Results revealed that management succession variables, namely; training the successor, successor involvement in business management and successor factors-work fit had a positive and significant relationship with the survival of FOMBs. However, the internal recruitment of the successor had an insignificant relationship with the survival of FOMBs. Therefore, management succession planning sustains the leadership pipeline and survival of the FOMBs through the involvement of the successor in business management, sufficiently training the successor, and handing over power to the successor whose competency and factors fit with the relevant work. The study contributes to an understanding of management succession planning variables and how they relate to the survival of family-owned manufacturing businesses. The study also provides a new conceptual framework on transgenerational management succession planning in the FOMBs
Factors affecting sales of international solar mini-grids in Tanzania mainland
Full text linkThe research purpose was to investigate factors that affect Sales of International Solar Mini-Grids in Tanzania Mainland. The motivation for the study was because there was evidence of a decline in sales of International Solar Mini-Grids in Mwanza, Dar es Salaam, and Arusha regions. The study used a sample size of 70 respondents, a cross-section survey, primary data, and secondary data. The study used the mixed methods research design. Multiple linear regression was employed in quantitative data analysis with the aid of SPSS. Thematic analysis was conducted to derive themes from the qualitative data and information obtained was utilized to supplement the quantitative data. The study revealed that government policies, more specifically energy policy, significantly affect sales of International Solar Mini-Grids in Tanzania Mainland. In addition, the regulatory framework, particularly tariff, significantly affects sales of International Solar Mini-Grids. Also, customers’ purchasing tendencies were significantly affecting the sales of International Solar Mini-Grids. The findings imply that ignoring the factors affecting sales of International Solar Mini-Grids in Tanzania Mainland might worsen the power sector and solar Mini-Grids sustainability. This work recommends that to foster the sales of International Solar Mini-Grids, the government should have a suitable energy policy and regulatory framework geared to enhance the marketability of electricity and enhance customer purchase. The study contributes to knowledge by offering empirical evidence on renewable energy that will be of paramount importance to other renewable energy stakeholders
Evaluating Machine Learning Approaches in Structural Equation Modelling to Improve Predictive Accuracy in Marketing Research
Full text linkBackground: This study aimed to fill a critical research gap by comparing traditional Structural Equation Modelling (SEM) with hybrid Bayesian-Machine Learning (ML) models in marketing research, focusing on the limited exploration of these advanced techniques.Purpose: This study aimed to evaluate the effectiveness of integrating Bayesian SEM with advanced machine learning techniques to enhance predictive model performance, manage complex data structures, and improve marketing applications.Design/methodology/approach: The study employed a systematic comparative research design to assess the predictive accuracy and robustness of traditional SEM in comparison to hybrid Bayesian-(Bayesian-ML) models. A rigorous review of 262 scholarly articles from major databases was conducted, with 23 studies meeting inclusion criteria to inform the model development and evaluation. Findings/Result: The findings show that traditional SEM excels in theoretical modelling and interpretability but lacks predictive accuracy and robustness, which Bayesian SEM improves by using prior distributions. ML techniques further enhance predictive accuracy and robustness, while hybrid models combining Bayesian SEM with ML achieve the highest levels of both.Conclusion: Adopting hybrid models can substantially enhance the predictive accuracy of marketing outcomes and the robustness of model analyses.Originality/value (State of the art): This study contributes to knowledge by advancing methodological approaches through challenging existing data analysis paradigms, methods and approaches and therebefore offering practical guidance for future studies.
Keywords: accuracy, bayesian methods, hybrid models, machine learning, predictive, robustness, structural equation modelling (SEM
Service quality and customer satisfaction in the airline industry in Tanzania: a case of Air Tanzania Company Limited
Full text linkThis study aimed to assess the influence of service quality on customer satisfaction within Air Tanzania Company Limited (ATCL) in Dar es Salaam, with a specific focus on the influence of tangible elements, personal services, and airline image. The study adopted a theoretical framework based on the Expectancy Disconfirmation Theory and the AIRQUAL Model for understanding the relationship between service quality and customer satisfaction. To achieve the study’s objectives, a cross-sectional research design was employed, allowing for the collection of data from a diverse sample of ATCL customers. The sample was selected using a combination of simple random sampling and purposive sampling techniques. A total of 302 ATCL customers and 8 supervisors from ATCL participated in the study, providing valuable insights into their perceptions of service quality and its effect on their overall satisfaction. Data collection was primarily conducted through structured questionnaires and face-to-face interviews. The data was analyzed using Binary Logistic Regression in IBM SPSS Statistics 23, allowing for the identification of significant relationships between service quality dimensions and customer satisfaction. The analysis of perceived service quality dimensions showed that customers\u27 perceptions of ATCL’s service quality fell short of their expectations, with negative scores across all dimensions. This suggests a general dissatisfaction among customers with the service quality provided by ATCL. Specifically, the rankings indicated that airline image was the top contributor to dissatisfaction. The overall index score for service quality further supported these findings, registering at -0.3996. The binary logistic regression results indicated significant positive relationships between all three dimensions (tangible elements, personal services, and airline image) and customer satisfaction. To maintain service quality standards, collaboration between policymakers and ATCL management is crucial to establishing guidelines as well as conducting regular audits, allocating enough resources for tangible improvements and investing in employee training for better customer interactions
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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