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Tour Company’s Service Quality and Tourists’ Revisit Intention in Arusha Region Tourist Destinations Majaliwa, Dioscory; Magasi, Chacha
Journal of Consumer Sciences Vol. 9 No. 1 (2024): Journal of Consumer Sciences
Publisher : Department of Family and Consumer Sciences, Faculty of Human Ecology, IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jcs.9.1.1-21

This study investigated the effect of tour companies’ service quality on tourists’ intention to revisit tourism destinations in the Arusha region. The general objective of this study is to examine the effect of tour companies’ service quality on tourists’ revisit intentions in Arusha tourist destinations. This study used a cross-sectional research design and employed a survey as the data-collection method. Respondents were selected using simple random sampling; 384 respondents were included in this study. Questionnaires were used to collect data from respondents at Arusha tourist destinations. Data were analyzed using descriptive statistics and a binary logistic regression model. The findings revealed that tangibles, responsiveness, and assurance had positive indices, implying that tourists were delighted by the service provided. The study establishes a positive relationship between tangibles, responsiveness, and assurance dimensions and tourists' revisit intentions, with a specific emphasis on the statistically significant connections of tangibles and responsiveness at p < 0.05, emphasizing the need to enhance these aspects to promote repeat visits to Arusha tourist destinations. However, assurance was found to have an insignificant relationship with tourists’ intentions to revisit. Therefore, tour companies, government entities, and tourism authorities should focus on improving tangibles and responsiveness dimensions to enhance tourists' intention to revisit.

Tour Company’s Service Quality and Tourists’ Revisit Intention in Arusha Region Tourist Destinations Majaliwa, Dioscory; Magasi, Chacha
Journal of Consumer Sciences Vol. 9 No. 1 (2024): Journal of Consumer Sciences
Publisher : Department of Family and Consumer Sciences, Faculty of Human Ecology, IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jcs.9.1.1-21

This study investigated the effect of tour companies’ service quality on tourists’ intention to revisit tourism destinations in the Arusha region. The general objective of this study is to examine the effect of tour companies’ service quality on tourists’ revisit intentions in Arusha tourist destinations. This study used a cross-sectional research design and employed a survey as the data-collection method. Respondents were selected using simple random sampling; 384 respondents were included in this study. Questionnaires were used to collect data from respondents at Arusha tourist destinations. Data were analyzed using descriptive statistics and a binary logistic regression model. The findings revealed that tangibles, responsiveness, and assurance had positive indices, implying that tourists were delighted by the service provided. The study establishes a positive relationship between tangibles, responsiveness, and assurance dimensions and tourists' revisit intentions, with a specific emphasis on the statistically significant connections of tangibles and responsiveness at p < 0.05, emphasizing the need to enhance these aspects to promote repeat visits to Arusha tourist destinations. However, assurance was found to have an insignificant relationship with tourists’ intentions to revisit. Therefore, tour companies, government entities, and tourism authorities should focus on improving tangibles and responsiveness dimensions to enhance tourists' intention to revisit.

Unlocking Students’ Enrolment: A Mixed Methods Study on How Brand Reputation and Perceived Benefits Shape Higher Education Choices in Tanzania Magasi, Chacha; Bwemelo, Gordian Stanslaus
Indonesian Journal of Social Research (IJSR) Vol 6 No 3 (2024): Indonesian Journal of Social Research (IJSR)
Publisher : Universitas Djuanda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30997/ijsr.v6i3.511

As competition for student enrolment intensifies, higher education institutions must understand the factors influencing students' choices to ensure their sustainability and growth. The study investigated how brand reputation and perceived benefits affect higher education enrolment intention. The study employed a concurrent mixed-methods approach, combining quantitative data from surveys with qualitative data from Focus Group Discussions (FGDs) to comprehensively understand the research problem through a triangulation approach. The first objective involved conducting qualitative exploration through seven purposively selected focus group discussions (FGDs), applying thematic analysis to identify factors influencing enrolment choices. The second objective involved utilizing structured questionnaires to collect quantitative data from a representative sample of 119 randomly selected respondents. Multiple linear regression analysis was employed to analyze quantitative data and examine how brand reputation and perceived benefits influence enrolment intentions. The qualitative findings indicate that brand reputation, alum success, campus facilities, faculty expertise, financial aid, and academic programs are pivotal in shaping students' choices. Conversely, the quantitative analysis reveals that while brand names and compelling slogans positively affect enrolment intentions, brand logos do not yield a significant impact. These findings underscore the need for higher education institutions to prioritize brand reputation, alumni engagement, investment in campus facilities and faculty expertise, and financial support to enhance student attraction. This research extends brand equity theory to the higher education context, elucidating the significance of branding in enrolment decisions and enhancing academic discourse through its dual-method approach. The findings conclude that effective branding is a critical determinant of student enrolment choices, thereby offering substantial contributions to developing higher education marketing strategies.

Evaluating Machine Learning Approaches in Structural Equation Modelling to Improve Predictive Accuracy in Marketing Research Magasi, Chacha
Indonesian Journal of Business and Entrepreneurship Vol. 11 No. 1 (2025): IJBE, Vol. 11 No. 1, January 2025
Publisher : School of Business, IPB University (SB-IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17358/ijbe.11.1.93

Background: 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)

Cultivating Future Graduate Entrepreneurs: A Holistic Exploration of Vital Entrepreneurial Skills from a Tripod-Based View and Evidence Magasi, Chacha
SEISENSE Journal of Management Vol. 8 No. 1 (2025): SEISENSE Journal of Management
Publisher : SEISENSE (PRIVATE) LIMITED

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33215/8wpf1244

Purpose- 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.

Reimagining Consumer Analytics: Predictive and Real-Time Insights Through Dynamic Structural Equation Modeling Magasi, Chacha; Nyamwesa, Aloyce M.
Indonesian Journal of Business and Entrepreneurship Vol. 11 No. 3 (2025): IJBE, Vol. 11 No. 3, September 2025
Publisher : School of Business, IPB University (SB-IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17358/ijbe.11.3.734

Background: Prior research had predominantly emphasized traditional Structural Equation Modeling (SEM), with limited exploration of dynamic SEM. Yet, dynamic SEM was essential, as it enhanced the precision of real-time consumer behavior prediction. Objectives: This study critically examined recent advances in dynamic SEM, focusing on their effectiveness in improving predictive accuracy, model efficiency, and adaptive decision-making in response to temporal variations in consumer behavior.Design/methodology/approach: A review of peer-reviewed empirical studies published between 2010 and 2025 was conducted. Using predefined inclusion and exclusion criteria, relevant works were retrieved from Scopus and Web of Science. Comparative synthesis highlighted differences between traditional and dynamic SEM applications.Findings/Results: The results demonstrate that dynamic SEM substantially outperforms traditional SEM by incorporating temporal dynamics, capturing interindividual variations, and effectively managing intensive longitudinal data. Its strength lies in analyzing large-scale, high-frequency datasets from digital platforms such as Google Analytics, enabling accurate prediction and monitoring of consumer behavior over time. The study further contributes original constructs - including behaviorally relevant triggers, sentiment indicators, personalization measures, and engagement metrics - thus extending the scope of consumer analytics.Conclusion: Dynamic SEM was shown to exert a transformative impact on consumer behavior research and marketing management by supporting real-time behavioral adjustments and agile decision-making. However, challenges remained regarding its computational capacity with large and complex datasets, underscoring the need for advanced data governance and sophisticated analytical tools.Originality/value: The study evaluated the methodological innovations in a unique and systematic way and gave an advice on how to improve the SEM applications and theory when handling large and complex datasets when dealing with the temporal changes in consumer behavior. Researchers, policy-makers and practitioners were given the actionable recommendations on how to improve and utilize the dynamic SEM as a future-proof marketing analytics approach. Keywords: big data analytics, dynamic structural equation modelling, latent growth modeling, marketing decision-making, temporal dynamics

ASSESSING PRESIDENT SAMIA SULUHU HASSAN’S LEADERSHIP IMPACT ON TANZANIA’S SOCIO-ECONOMIC DEVELOPMENT: AN ANALYSIS OF STRATEGIC INITIATIVES AND POLICY OUTCOMES Magasi, Chacha
Journal of Social Political Sciences Vol 5 No 4 (2024): November 2024
Publisher : Universitas Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52166/jsps.v5i4.239

The purpose of this study is to provide a rigorous evaluation of President Samia Suluhu Hassan’s leadership, focusing on its broader impact on Tanzania’s socio-economic development. As the first female president of Tanzania, her administration marks a critical juncture in the nation’s history, facing both significant challenges and opportunities for transformative change. This research examines her strategic efforts in economic recovery, infrastructure development, and the management of the COVID-19 pandemic, assessing how these policies have influenced public health outcomes, economic growth, and governance. Additionally, the study explores her initiatives to advance gender equality, particularly addressing the persistent disparities in both urban and rural areas. A mixed-methods approach was employed, combining quantitative data on economic performance, public health metrics, and gender representation with qualitative insights gathered from focus group discussions involving policymakers, analysts, and experts. The findings reveal notable progress under President Hassan’s leadership in areas such as economic recovery, gender equality, and infrastructure development, particularly through projects like the Standard Gauge Railway (SGR) and the Julius Nyerere Hydropower Station. However, challenges such as financial constraints and project delays remain. The study’s novelty lies in its comprehensive analysis of President Hassan’s multifaceted policy impacts, contributing new knowledge to the discourse on governance, sustainable development, and gender equality. Key implications include recommendations for enhanced infrastructure investment, improved pandemic preparedness, and targeted support for small and medium-sized enterprises (SMEs).

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