Factor Analysis Techniques Research Articles

Identify Obstacles in Implementing Total Quality Management Framework in the Ghanaian Construction Sector using Exploring Factors Analysis Technique

The concept of total quality management improves an organization’s performance, but there are several obstacles to its practical application. This study therefore identifies the obstacles to implementing the Total Quality Management (TQM) framework in the Ghanaian construction sector. A survey questionnaire was employed for the study, and the results were based on responses from 536 of 641 questionnaires sent out to the top management in the Ghanaian construction sector. The sample frame for the study was determined from the population made up of one thousand two hundred and eighty-two (1282) small to large-sized (D4K4 to D1K1) good-standing construction firms registered with the Association of Building and Civil Engineering Contractors of Ghana (ABCECG). The data was analysed using the Exploratory Factor Analysis (EFA) technique. Cronbach's alpha was used to measure the reliability of the study instrument. While the Kaiser-Meyer-Olkin and Bartlett's tests of sphericity were employed to assess sampling adequacy and significance. The study identified sixteen obstacles in implementing TQM framework in the Ghanaian construction sector. The five most significant potential obstacles among the sixteen identified obstacles in the ranking were: lack of understanding of TQM; lack of enforcement by the agencies responsible for regulating the application of TQM; inadequate TQM systems; lack of enthusiasm for TQM implementation; and lack of a TQM policy. All sixteen items (obstacles) identified were found to have a high impact on TQM implementation in the Ghanaian construction sector. Hence, understanding these identified obstacles to TQM implementation will enable construction managers to develop more effective strategies for improving TQM implementation in the Ghanaian construction sector. The study contributes to existing literature by using exploratory factor analysis techniques to identify obstacles to total quality management implementation in the Ghanaian construction sector.

Islamic Entrepreneurial Marketing Orientation Among Islamic University Students

Indonesia plans to be the number one global halal hub that need support of massive Islamic entrepreneurial marketing capabilities. This study aims to assess Islamic entrepreneurial marketing orientation among university students. The sample used was students of the Faculty of Economics and Islamic Business UIN Prof. K.H. Saifuddin Zuhri Purwokerto who had participated in a business internship program (PMBM). Data were collected using questionnaire instruments and analyzed using Confirmatory Factor Analysis technique. The results revealed that Islamic entrepreneurial marketing orientation proved to be a multidimensional construct consisting of factors such as: Activeness, Opportunity orientation, Risk orientation, Innovation orientation, Customer orientation, Value orientation, Committed and Shari'ah conformance. The results showed that the dimensions of Islamic entrepreneurial marketing orientation of respondents were generally quite good. This can be seen from the percentages that are above the 70% criterion). As for the dimensions that are still low are proactiveness (64%) and risk orientation (59%). This study provides novelty by finding that the implementation of sharia conformance is proven to be important in building Islamic entrepreneurial marketing orientation among Islamic students in Islamic university. However, other factors need to be emphasized more in the development of the programme since the results show that other factors are stronger in forming the students orientation in Islamic entrepreneurial marketing. Future research can be conducted by developing similar research on Islamic students in other region and in privat university.

Air nanobubble water improves plant uptake and tolerance toward cadmium in phytoremediation

Heavy metal contamination continues to be a persistent environmental problem. To address this issue, this study evaluated the impact of air nanobubbles (NBs) in water on the uptake of heavy metals by Alternanthera philoxeroides (A. philoxeroides), a common aquatic plant in China known for its rapid growth, strong vitality, and high capacity for heavy metal remediation. This study found that diluted air NBs (25% concentration) boosted cadmium uptake of A. philoxeroides by 17.39%. They also enhanced plant growth (25–50%) and photosynthetic pigments (10–20%) even at low cadmium levels (0.1 mM). Furthermore, the incorporation of 25% air NBs has been demonstrated to significantly amplify the performance of key antioxidant enzymes, such as superoxide dismutase and catalase, alongside heightened levels of crucial antioxidants such as malondialdehyde. This heightened activity of antioxidant defenses offers a compelling explanation for the potential amelioration of cadmium toxicity and concurrent enhancements in overall plant growth rates. Notably, a comprehensive analysis utilizing the excitation emission matrix–parallel factor analysis (EEM-PARAFAC) technique has revealed alterations in the composition of rhizosphere dissolved organic matter due to the presence of NBs. This ncomposition change of the rhizosphere dissolved organic mattermposition has subsequently exerted an influence on plant complexation processes and the subsequent uptake of cadmium. This study demonstrates that the strategic implementation of air NBs in water systems holds the potential to significantly enhance the plant's ability to detoxify cadmium and improve the uptake of heavy metals during phytoremediation processes.

Urban Living With Style: An Exploratory Survey of Bangkok Generation Y’s Lifestyle

This study is a preliminary exploration of the lifestyle typologies of Generation Y in Bangkok, Thailand. Drawing upon an AIOs (Activities, Interests, Opinions) approach, 126 statements were developed to segment them into groups. A field survey was employed through questionnaires to collect data from this cohort. A total of 455 responses were analyzed through an exploratory factor analysis (EFA) technique. Eight distinct lifestyle segments were identified: the On-trend Netizens, Adrenaline-addicts, Self-care Traditionalists, Concerned Pragmatists, Safe-centered Family Person, Materialists, Emotional Facebookers, and Soap Haters. Each segment has unique characteristics. The findings show the nuances of the lifestyles of Generation Y in Bangkok, laying the foundations for a better understanding of this group. It is beneficial for marketing practitioners to develop appropriate communication strategies, products, and services accordingly.

Predicting academic performance of learners with the three domains of learning data using neuro-fuzzy model and machine learning algorithms

In recent days, learners faced difficulties learning programming courses. This research study will help the learners learn complex concepts quickly with different activities like flipped classrooms, online quizzes, learning by doing, and a virtual laboratory. This research is carried out to address the difficulties of learners and cover all the domains of learning, including knowledge, Skill, and Attitude. The fuzzy logic method has recently been applied in education to overcome these restrictions. While employing the fuzzy logic approach to evaluate student achievement, qualifications are assessed qualitatively rather than quantitatively. This research study applies Fuzzy Logic in the first stage, Factor Analysis (FA), and Machine Learning (ML) techniques in the second stage to discover essential factors associated with the effective use of Active Learning Strategies (ALS) in the Learning Management System (LMS) of information technology course learners. Fuzzy logic and neural network topology can be coupled using ANFIS, an adaptable network. FA is performed to find the critical factors for successful learners. The study compares the performance of five supervised machine learning algorithms: K-Nearest Neighbor, Decision Tree, Naive Bayes, Discriminant Analysis, and Support Vector Machine. These classifiers are evaluated to determine their suitability and model fit in the context of the research. In this study, real-time data is collected from B.Tech Information Technology learners. The following prediction models achieved high accuracy before FA analysis: Naive Bayes (90 %), Support Vector Machine (89 %), Discriminant Analysis (88 %), Decision Tree (86 %), and K-Nearest Neighbors (82 %). Naive Bayes gives the best accuracy, with 90 %. Following factor analysis (FA), the accuracy achieved by various classifiers is as follows: Naive Bayes - 92 %, K-Nearest Neighbors - 92 %, Support Vector Machine - 90 %, Discriminant Analysis - 89 %, and Decision Tree - 88 %. Among these, Naive Bayes and K-Nearest Neighbors exhibit the highest accuracy of 92 %.

A new territorial attractiveness index at the international scale: design, application and patterns in Italy

The attractiveness of regions and territories for firms, investments, tourists, students, talented people, and other categories is a relevant issue for regional economic development, due to the increasing importance of the relationships and flows on the global scale. The growing concern about this question requires a new comprehensive analytical approach that goes beyond partial approaches. The construction of a synthetic index that measures the territorial attractiveness from a multidimensional perspective is the strategy presented in this work to deal with this issue from a new point of view. We first introduce and present our methodological approach for the construction of the synthetic index, which makes use of both qualitative (budget allocation process) and quantitative (factor analysis) techniques. Our synthetic index is based on the main indicators about incoming flows from abroad (FDIs, workers, tourists, university students). Secondly, we illustrate and discuss the results of its application to the case of the international attractiveness of the Italian regions, based on an 8-year long dataset. The findings reveal that the North–South gap, the well-known Italian spatial pattern, is not fully satisfying to read and interpreter the geographical imbalances in terms of multidimensional territorial attractiveness. Thanks also to the calculation of the Moran’s Index, we show the complexity of the Italian economic geography.

Factors Influencing Ethnic Minority Students’ Programme Development Capacity: Case Study at Pedagogical Universities in Vietnam

Educational programme development capacity is one of the indispensable competencies of teachers today. This competency should be developed early on for students enrolled in pedagogical universities. In this regard, ethnic minority students need more attention than ethnic majority students. The goal of this study was to look into the various factors that affect the ability of ethnic minority students enrolled in pedagogical universities in Vietnam to develop educational programmes. This was done in order to assist ethnic minority students and their parents, which necessitated pedagogical universities as well as administrators having a scientific foundation in studying and training students to meet the requirements of society. In this study, a quantitative research methodology was employed. Data were collected from a sample of 324 students using a survey (from March 13 to 27, 2023). Cronbach‘s Alpha test () and Exploratory Factor Analysis (EFA) techniques were used to evaluate and build the scales. The reliability and construct validity of the scales were also assessed using Cronbach’s  and EFA respectively. Multiple linear regression was also used to determine the variables that affect students’ ability to design programmes. The findings of the research indicated that there were four groups of factors that affected students’ programme development capacity: individual factors, family factors, school factors and social factors. Among these, family factors were found to exert the greatest influence (Beta coefficient equal to 0.556), while social factors had the smallest impact (Beta coefficient equal to 0.276) on students’ programme development capacity. The research results provide a scientific basis for the development of programmes and policies to support ethnic minority students, enhance their educational capacity and meet the objectives of general education in Vietnam.

Does GCG moderate the financial distress on tax avoidance?

This study aims to determine the effect of financial distress on tax avoidance, moderated by good corporate governance. This research was conducted on transportation and logistics sector companies listed on the Indonesia Stock Exchange in 2019–2021 because the Indonesian economy began to experience a contraction as a result of the COVID-19 Pandemic in 2019 and continued until 2021, therefore it has an impact on state tax revenues. The sample was selected using a purposive sampling technique, and 14 companies were identified. The data analysis technique used is moderation regression analysis. This study also uses factor analysis techniques to find the best factors to serve as proxies for corporate governance. The results of the study show that financial distress has a positive effect on tax avoidance. This study also found that good corporate governance which is proxied by an independent board of commissioners can weaken the effect of financial distress on tax avoidance. The increasing financial distress in companies, the practice of tax avoidance is also increasing. If the company implements good governance, the management will make less effort to tax avoidance. This is because the more the number of independent commissioners, the more effective it is in supervising the performance of managers.

Likert scales and questions: uses and abuses

when conducting business and management research, the most common strategy employed for collecting primary data is either interviews or questionnaires (or both). When questionnaires are used to collect primary data a very common approach used is to construct questions which can be called Likert-type questions or Likert scales. Numbers are allocated to the question responses of each question.. Often, this is followed by performing arithmetic or statistical operations on the allocated numbers. In many cases encountered by the author, the analysis has even included techniques such as parametric statistics and factor analysis. This paper explains why such simplistic approaches are completely invalid and should never be used. It goes on to explain how analysis can be done whilst avoiding typical hazards. Often, the writers of such papers do not understand or explain levels of measurement. Of course, Likert scales are at an ordinal level of measurement which would normally preclude the use of arithmetic, statistical, factor analysis techniques there is an additional problem of reliability because different people will interpret terms such as strongly disagree and disagree, differently. Likert was aware of these problems when writing the original paper in 1932 although at that time the term “levels of measurement” was not in use. This paper provides approaches and suggestions for avoiding the problems of data analysis when using Likert-type questions. This paper should be of assistance to those who intend to use Likert-type questions in the questionnaire.

Adoption intention of mobile QR code payment system among marginalized street vendors: an empirical investigation from an emerging economy

PurposeRecently, the Government of India has emphasized digital financial inclusion for promoting cashless transactions with a vision to transform India from a traditional cash-based economy into a cashless economy. Technology-driven payment apps are facilitated greater access to cashless financial services and improve the speed, efficiency, accuracy and effectiveness of financial transactions. This study aims to explore the determinants of quick response (QR) code mobile payment (m-payment) adoption intention among marginalized street vendors in India.Design/methodology/approachThe proposed research model was tested using 320 responses from QR code m-payment users. An interview schedule was performed using the structured questionnaire from marginalized street vendors by adopting a purposive sampling technique. The proposed research framework of this study developed on the Unified Theory of Acceptance and Use of Technology (UTAUT). In addition to the existing variables proposed in the UTAUT model, three more variables have been added, namely, digital financial literacy (DFL), personal innovativeness (PI) and perceived trust (PT). Besides, the study used confirmatory factor analysis and structural equation modeling techniques to analyze the data.FindingsThis study confirms that factors such as performance expectancy, effort expectancy, facilitating conditions, PT and customers’ DFL are significant determinants of street vendors’ intention to use QR code m-payment services. However, social influence and PI have shown an insignificant relationship with adopting a QR code m-payment system.Research limitations/implicationsThe results provide insights for policymakers and service providers. Specifically, government and bankers design promotional campaigns emphasizing the ease of use, perceived benefits, security and faster business transactions to accept and use the QR code m-payment system to encourage prospective users to achieve a cashless economy.Originality/valueMany prior studies have widely concentrated on m-payment adoption intention in India. However, only a few studies have attempted to examine the factors influencing the adoption of QR code m-payment services among merchants from emerging economies. There is a dearth of studies on QR code adoption from an unorganized sector perspective, specifically marginalized street vendors. Therefore, this study explicitly examines the extent to which the determinants of adoption intention toward QR code-based m-payment services among marginalized street vendors within the framework of the extended UTAUT model by incorporating DFL, PI and PT. The findings of this study contribute, theoretically and practically, to the existing literature.

Investigating practical wisdom in complex system management: What is it and how do we get more?

AbstractSystems are now extremely complex with the continuous involvement of multiple stakeholders and rapidly advancing technology, and a new way of viewing high‐performance system management and decision‐making is needed. This paper considers the use of practical wisdom as a promising way of revitalising system management to improve the success rate in making critical decisions. Practical wisdom has been investigated as a useful approach in many fields, including philosophy, psychology, health, education and organisation studies: however, its application to system management is sparse. Questionnaires were sent to 124 manager participants to assess their view of the importance of various practical wisdom attributes as these relate to system management success. Applying the exploratory factor analysis technique emerged the following factors: (1) practical mindset; (2) stakeholder mindset; (3) moral mindset; (4) win‐win mindset; and (5) holistic thinking mindset. Two of these factors, stakeholder mindset and win‐win mindset, have not previously emerged in practical wisdom research. The factors extracted were validated via both technical techniques and considered commentary by senior leadership practitioners. The results of this study can assist managers to develop greater insight into optimal management of increasingly complex systems via consideration of these practical wisdom factors and the interplay between them.

Prediction of Purchase Intention for Medical Cannabis Products: Case Study in Medellín Colombia

This article provides information on the level of acceptance of medical cannabis, the intention to use it and the factors involved in the decision-making process of individuals. Despite the studies developed for the use of medicinal cannabis, it has some difficulties to enter the market due to existing prejudices as a recreational drug. In order to provide valuable information to make the right decisions and generate marketing strategies, the relationships between the use of medical cannabis and the Theory of Planned Behavior in the purchase and consumption decision are explored using factor analysis techniques, and relevance analysis. Besides, a purchase intention prediction model based on machine learning is proposed. The results show that the dimensions ”attitudes” and ”perceived behavioral control” have a positive and statistically significant relationship with consumption and purchase. The purchase intention prediction model achieved a performance with an accuracy greater than 94%.

The effects of advanced factor analysis approaches on outcomes in randomised trials for depression: protocol for secondary analysis of individual participant data.

Modern psychometric methods make it possible to eliminate nonperforming items and reduce measurement error. Application of these methods to existing outcome measures can reduce variability in scores, and may increase treatment effect sizes in depression treatment trials. We aim to determine whether using confirmatory factor analysis techniques can provide better estimates of the true effects of treatments, by conducting secondary analyses of individual patient data from randomised trials of antidepressant therapies. We will access individual patient data from antidepressant treatment trials through Clinicalstudydatarequest.com and Vivli.org, specifically targeting studies that used the Hamilton Rating Scale for Depression (HRSD) as the outcome measure. Exploratory and confirmatory factor analytic approaches will be used to determine pre-treatment (baseline) and post-treatment models of depression, in terms of the number of factors and weighted scores of each item. Differences in the derived factor scores between baseline and outcome measurements will yield an effect size for factor-informed depression change. The difference between the factor-informed effect size and each original trial effect size, calculated with total HRSD-17 scores, will be determined, and the differences modelled with meta-analytic approaches. Risk differences for proportions of patients who achieved remission will also be evaluated. Furthermore, measurement invariance methods will be used to assess potential gender differences. Our approach will determine whether adopting advanced psychometric analyses can improve precision and better estimate effect sizes in antidepressant treatment trials. The proposed methods could have implications for future trials and other types of studies that use patient-reported outcome measures.

Coping with Transgressions by the Romantic Partner: An Inventory Validation and its Correlation with Forgiveness

Almost every person has to deal with transgressions committed by a romantic partner and faces their negative psychological outcomes, and coping strategies might be key to understanding post-transgression dynamics and forgiveness. We tested the construct validity of the Inventory of Strategies for Coping with a Partner's Transgression which include the emotion (E-FCS), problem (P-FCS), and meaning-focused coping strategies (M-FCS) scales. Results replicated the factor structure of each of the three scales through confirmatory factor analysis techniques, tested its reliability with the McDonald’s omega coefficient, and then correlated the scales with forgiveness and resentment, strengthening its construct validity. In general, the validity and reliability of scales were confirmed. Emotion-focused strategies showed a negative correlation with forgiveness, while problem and meaning-focused strategies had a positive correlation. These findings were discussed in the context of theory and their practical implications.

FAKTOR YANG MEMPENGARUHI KEPUTUSAN WISATAWAN DOMESTIK KE CAFE EL LAGO, KINTAMANI, BALI

Pandemic has a major impact on the tourism sector in Bali, many of tourist attractions are closed due to the effect of Covid-19 and some of it turn to a restaurant or cafe business, one of popular cafe is Cafe El Lago which has a unique buildings and located near Batur mountain and it is suitable as a place for relaxation. The purpose of this study is to find out the characteristics and factors that influence the decision of domestic tourists to visit Cafe El Lago. The sample in this study is 100 domestic tourists with sampling techniques is purposive sampling. Data was taken in this study by using observation techniques, questionnaires, documentation and literature studies. Data were analyzed using validity tests, reliability tests and factor analysis techniques. The results showed that there are 6 variable factors that affectingdomestic tourists from 23 indicators. The six (6) factors have eigenvalue > 1 with a cumulative eigenvalue value of 63,32%.The most dominant factor from overal factors is service factor has an eigenvalue value of 6,99 with a total variance of 16,71% consists of six forming indicators consisting of (1) speed, (2) friendliness. (3) accuracy, (4) directions. (5) quality, (6) availability of transportation and this factor is the main factor that affect domestic tourists visiting Cafe El Lago Batur Selatan, Kintamani, Bangli, Bali.

Assessment of Construction Risks in Projects Funded by External Sources in Jordan during the COVID-19 Pandemic

In general, construction projects are vulnerable to various risks during their life cycle. These risks may negatively affect the project cost and duration, in addition to other factors, including environmental impact, health and safety, and quality of construction work. The COVID-19 pandemic has brought more challenges to construction projects. This study presents an assessment of 47 major risks affecting construction projects. The research investigates and assesses the risk factors associated with a special type of construction project, namely, projects funded by external sources, due to their importance, characteristics, and sensitivity. Furthermore, the study was carried out under the impact of the special conditions and constraints associated with the COVID-19 health pandemic. These conditions provided specific types of risks, results of risk assessment, and recommended responses to the risks. The studied risks were categorized using the PESTLE technique, an external factor analysis technique, which includes six groups of Political, Economic, Social, Technological, Legal, and Environmental risks. A questionnaire survey was conducted on 34 construction organizations that implemented or supervised projects funded by external sources. The aim of the survey was to assess the risks affecting the construction projects in terms of probability of occurrence and severity on the projects’ cost and time schedule. Then, the importance of each risk was calculated, and the risks were ranked according to their importance. The results showed the high importance of environmental and legal risks and indicated that the most important risk factors are the difficulty of issuing licenses and permits and the inappropriate definition of the scope of work. This study would help managers and fund providers make decisions regarding risks during uncontrolled pandemic or disastrous circumstances. Although the current study was conducted in Jordan, its procedures and results can be useful in other locations with different properties and conditions.

Factor analysis for signal modeling and noise characterization in spectro-kinetic data

Measurement signals and noise (heteroscedastic and homoscedastic) in different evolutionary spectral kinetic data sets are modeled and characterized by applying maximum likelihood common factor analysis (MLFA) and principal axis factoring (PAF), as factor-based techniques. They decompose data into common and specific factors, that are assumed to be constant heteroscedastic. The digital filter is also used for characterization of noise in data and to confirm the obtained results from factor analysis techniques. No one of the applied methods requires the use of replicated measurements. Inverted Blackman windowed sinc (BWS) smoothing coefficients as high-pass digital filters are employed to provide point and bin estimates of noise from measurement vectors without any assumption about noise structure. The proportionality of noise to signals and their characteristics are also reported and are comparable when applying different methods.The proposed methods are compared using both simulated and experimental kinetic data sets. Experimental data includes fluorescence and UV–vis absorbance kinetic spectra. A simple solution for problem of MLFA application to fat data is proposed and successfully applied. Different types of independent noise including identical independent distribution (iid), constant heteroscedastic, and general heteroscedastic are added to the simulated data, in various levels.In the case of iid noise results from all methods are almost the same. In the presence of heteroscedastic noise results from MLFA and PAF are preferred to PCA regarding subspace angles and discrepancy function values. Employment of methods for highly overlapped, skinny, and fat data shows the superiority of MLFA to PAF and PCA. The independent noise characteristics obtained from factor analysis methods are comparable to that from digital filters.

Between alternative and traditional social platforms: the case of gab in exploring the narratives on the pandemic and vaccines.

The phenomenon of deplatforming intended as the removal of social media accounts because of breaking rules on mainstream platforms such as Facebook, Twitter, YouTube, and Instagram recently increased due to new terms and conditions of use of digital media, and new alternative social media platforms emerged and presented themselves as protectors of freedom expression. In this way, it becomes interesting to understand better the context of these platforms' so-called web suburbs that consist in those digital places that ≪host what we can generally call "subcultures," including fandoms, religious sects, political extremists, and subcultures≫. Since April 2020, Gab can be considered the most widespread alternative platform in Western countries, with twenty million users daily, born as Twitter and Facebook alternative social media. The alternative social media platforms are intended as other connection services between users, which is halfway between a social media and a discussion forum born to boycott the censorship actions of the main social media platforms (Meta Group, Twitter, etc.) and celebrate free speech even on controversial positions. How are sensitive topics, such as the one that concerns the skepticism related to the approvals of vaccines during the pandemic, addressed on the alternative social media platform compared to how they are dealt with on the mainstream social media platforms? This explorative work wonders about the users' points of view on vaccine concerns and the relevant differences between Gab and Facebook in addressing this topic. The empirical part of this work has been set starting from the dataset composed of Gab and Facebook content posted between March 2020 and July 2021. The posts were extracted with web scraping techniques (for Gab) and proprietary data tools (for Facebook), querying the keywords: vaccine, vaccines, anti-vax (no-vax), Covid, Covid-19, coronavirus. The collection procedure considered the different platforms' structure and their different organization of the interaction spaces. The population consisted of 8000 English writers' posts, from which 2000 posts with the highest interaction value were extracted. The dataset was analyzed using Topic Modeling, Factor, and Classification Analysis techniques. Our work's methodological output deals with comparing these social media platforms, bearing in mind their ontological objects and their algorithms' role. From the analysis emerged the differences and similarities of the social media platforms in terms of the type of content published, rates of involvement, sources of information, and directions of the considered speech. These differences have been duly highlighted by three clusters related to discourse orientation and communication approach: Conflict of views, Emotional externalization, Recommendation and practices. In addition to the type of communication and information circulating on a powerful platform such as Gab, the results help us understand the different narratives promoted on the two social media platforms and their role in the possible promotion of the same sentiment, opinions, and ideological polarization.

Factors of Non-Muslim Customers Decision to Saving at Bank Syariah Indonesia (BSI)

Islamic banks are not specific to the Muslim community, but non-Muslims also use them. The customer certainly has a reason for deciding the choice of using Islamic banks. This study aims to analyze decision factors of non-muslim customers saving at Bank Syariah Indonesia (BSI) Ambon. The research is associative quantitative type by using survey methods that distribute questionnaires for data collection. The sample taken with probability sampling technique is 98 non-muslim customers. Then the data is processed by confirmatory factor analysis techniques. In analyzing the data, the authors used the help of SPSS 26 software. The results of the study show that decision factors of non-muslim customers save at Bank Syariah Indonesia (BSI) Ambon is (1) promotion as the first and strongest factor with an Eigenvalue of 4,855; (2) perception as the second factor that has an Eigenvalue of 2,120; (3) service as the third factor that has an Eigenvalue of 1,275; (4) location as the fourth factor with an Eigenvalue of 1,136.

Agricultural resources and practices in the circular bioeconomy adoption: evidence from a rural region of Greece

PurposeThis study aims to assess the factors influencing the adoption of circular bioeconomy practices by crop farmers.Design/methodology/approachData collected from 303 farmers in the region of Western Macedonia (WM) were used to identify the adoption factors of the circular bioeconomy. Principal component analysis (PCA) and exploratory factor analysis (EFA) techniques were applied through a custom-designed and specially structured questionnaire.FindingsThe results reveal four main motivations that lead farmers to adopt circular bioeconomy practices in their farming activities: interest in physical-economic resources and factors related to production and consumption; technology and renewable energy and the environment.Research limitations/implicationsThis study is based solely on farmers in WM. Furthermore, this study assumes that there will be a strategy to promote a circular bioeconomy under the auspices of the government.Originality/valueFew studies have focused on the perspectives of crop farmers and what encourages them to adopt circular bioeconomy practices in their crops. Existing barriers are related to economic incentives and constraints. The more circular bioeconomy practices farmers adopt, the greater the positive impact on the environment and rural development, and the factors influencing the adoption of these practices are investigated here.