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The literature includes several studies that define different critical success factors (CSF) which have to be considered to support the implementation of technology-enhanced learning (TEL) approaches. An analysis of such studies revealed that (1) regional differences seem to determine the CSF for TEL approaches, (2) certain CSF are relevant for TEL approaches in general, and (3) professionals in higher education determine which influential factors they consider when implementing TEL approaches. Thus, the question arises: in general, which influential factors do professionals in Austrian and German institutions of higher education actually consider when implementing TEL approaches?

The study is a quantitative research approach based on survey data.

The results show that certain influential factors seem to be generally important, such as the factors of respecting learning success or motivation. However, the outcome of the study also indicated that different moderating variables like experiences and personal relevance affect the professionals’ choices.

The originality and value are in the approach to identify generally important influential factors for the implementation of TEL approaches in Austrian and German institutions of higher education.

The purpose of this study is to identify the learner characteristics attributable to the likelihood and the duration of programme completion in the Bachelor of Science (BSc) and Bachelor of Technology Honours in Engineering (BTech) degree programmes of the Open University of Sri Lanka (OUSL).

Data were gathered from the re-registrants for the degree programmes in the academic year 2020/2021, using a questionnaire developed as a Google form. The sample consisted of 301 and 516 re-registrants from the BTech and BSc programmes respectively. Influential factors were identified using Kruskal Wallis test (for duration of completion), binary logistic regression (for likelihood of completion) and Chi-squared test (associations between presage and process factors).

Entry qualification, age and time management skills at entry had significant effects on duration of completion. Attendance at academic activities, organizing time for self-studies and the competency in English at enrolment had significant effects on the likelihood of completion. Prior open and distance learning (ODL) experience had no significant effect on any of the product factors considered.

Inaccessibility of dropouts and using only the responses from the first administration of the questionnaire are limitations. Active learners are more likely to respond, in the first administration and may bias the results.

Findings are useful for designing future studies to identify at-risk students and thereby enhance the programme completion and reduce prolonged time for completion.

Effective strategies to control the identified factors will uplift programme completion and reduce drop-out rates.

Decision making using inferential techniques makes the study distinct among studies undertaken on the same population. The study enriches the limited current research on factors affecting programme completion in ODL mode.

Since its development by Tinbergen (1962), the gravity model of international trade has widely been applied to analyse the effect of various factors on trade relationships between countries. Past studies on trade gravity vary not only in the mix of model variables but also in how they have come into the analysis. This study reviews existing literature on bilateral trade with an aim to identify influential predictors such as changes of trade policy and national development strategy and highlight important yet understudied factors such as transport and logistics infrastructure, and sustainable development. To demonstrate the needs to examine these critical factors across industry sectors, the study presents the case of textiles and clothing (T&C) production and trade between China and its trading partners as an illustration. Through the literature review, it shows how the gravity model can be applied to address current issues in international trade arena such as the potential trade war between the US and China, China’s Belt and Road Initiative (BRI), and other important factors shaping global T&C trade. This study offers future research directions for analysis of global trade in the T&C industry and contributes to the wider literature of international business and trade.

The recent promotion of prefabricated housing (PH) in China has resulted in a prosperous period for its implementation. However, transaction costs (TCs) cause low economic efficiency to stakeholders and hinder the further promotion of PH. No relevant study has yet been made to investigate the TCs and their causes in the PH field. This paper identifies critical TCs and explores the influencing factors from the developers' perspective.

Semi-structured interviews and a questionnaire survey were used to collect data about TCs and influencing factors. The most influential factors are identified with their impacts on particular TCs, yielded from correlation analysis and logistic regression.

From the developers' perspective in China's PH market, this study identified that the most concerning sources of TCs are: hidden costs arising from disputes, extra workloads from design changes, learning costs, intensive communication and coordination in assembly and unexpected information costs in decision-making. The use of an ordered logistic regression approach indicates that the four most influential factors are: qualification of the general contractor, mandatory local policies, owner type and competitiveness of the developer.

To reduce the TCs, experiencing learning and ensuring the design scheme's complicity are recommended to save information searching and exchanging costs. The implications for the PH developers are for them to: (1) professionalize their own organization and (2) procure high-qualified general contractors. For the policymakers, this means they should improve the clarity of the mandatory local policies for PH step-by-step.

By applying the TCs economic theory, this study explores factors that influence TCs in the PH industry. It sheds light on the influencing mechanism behind the TCs in the context of prefabricated housing.

This study aimed to identify and analyse the key factors influencing the adoption of e-government services and to discern their implications for various stakeholders, from policymakers to platform developers.

Through a comprehensive review of existing literature and detailed analysis of multiple studies, this research organised the influential factors based on their effect: highest, direct and indirect. The study also integrated findings to present a consolidated view of e-government adoption drivers.

The research found that users' behaviour, attitude, optimism bias and subjective norms significantly shape their approach to e-government platforms. Trust in e-Government (TEG) emerged as a critical determinant, with security perceptions being of paramount importance. Additionally, non-technical factors, such as cultural, religious and social influences, play a substantial role in e-government adoption decisions. The study also highlighted the importance of performance expectancy, effect expectancy and other determinants influencing e-government adoption.

While numerous studies have explored e-government adoption, this research offers a novel classification based on the relative effects of each determinant. Integrating findings from diverse studies and emphasising non-technical factors introduce an interdisciplinary approach, bridging the gap between information technology and fields like sociology, anthropology and behavioural sciences. This integrative lens provides a fresh perspective on the topic, encouraging more holistic strategies for enhancing e-government adoption globally.

Agri-food firms face many challenges when assessing and managing their performance. The purpose of this research is to determine important factors for an integrated agri-food supply chain performance measurement system.

This research uses the Peruvian kiwicha supply chain as a meaningful context to examine critical factors affecting agri-food supply chain performance. The research uses interpretative structural modelling (ISM) with fuzzy MICMAC methods to suggest a hierarchical performance measurement model.

The resulting kiwicha supply chain performance management model provides insights for managers and academic theory regarding managing competing priorities within the agri-food supply chain.

The model developed in this research has been validated by cooperative kiwicha associations based in Puno, Peru, and further refined by experts. Moreover, the results obtained through ISM and fuzzy MICMAC methods could help decision-makers from any agri-food supply chain focus on achieving high operational performance by integrating key performance measurement factors.

This paper aims to explore the phenomenon of impulse buying in the fashion industry. The online and offline channels are compared to determine which is perceived as leading to more impulsive buying.

As the result of the literature review, three research questions are proposed and examined through an online self-administered survey with 212 valid responses.

Results show that the offline channel is slightly more encouraging of impulse buying than the online channel; factors that encourage online impulse buying explain this behaviour to a greater extent than do discouraging factors; social networks can have a big impact on impulse buying.

Findings are limited by the sampling plan, the sample size and the measurement of some of the variables; only one product type is analysed. Further research is needed to confirm that shipping-refund costs and delayed gratification (traditionally, discouraging factors of online buying) encourage online impulse buying; clarify contradictory results regarding the role of online privacy and convenience. This research contributes to the validation of a scale to measure the influence of social media on impulse buying behaviour.

Offline companies can trigger the buying impulse to a greater extent than online retailers. Managers must carefully select social networks to encourage impulse buying, Facebook and Instagram being the most influential; Twitter has the least impact.

This study compares the impulse buying phenomenon in both the physical store and the internet. Moreover, the influence of social networks on impulse buying is also explored.

Este trabajo explora la compra por impulso en el sector de la moda, comparando los canales físico y online para determinar cuál se percibe como más impulsivo.

De la revisión de la literatura se extraen tres preguntas de investigación, examinadas a través de una encuesta auto-administrada online con 212 respuestas válidas.

Los resultados muestran que: el canal offline es ligeramente percibido como más impulsivo que el online; los factores motivadores de la compra impulsiva online explican mejor este comportamiento que los desmotivadores; las redes sociales pueden tener un gran impacto en la compra impulsiva.

Las limitaciones radican en el plan de muestreo, el tamaño muestral, y la medición de algunas variables; sólo una industria es analizada. Futuras investigaciones deberán: confirmar que los gastos de envío-devolución, así como la gratificación retrasada (tradicionalmente considerados como motivadores de la compra online) pueden motivar la compra impulsiva online; clarificar resultados contradictorios sobre la privacidad y la conveniencia de Internet. Esta investigación contribuye a la validación de un instrumento para medir la influencia de las redes sociales en la compra impulsiva.

Las tiendas físicas pueden estimular la compra por impulso más que los vendedores online. Los gestores deben seleccionar cuidadosamente las redes sociales para favorece la compra por impulso, siendo Facebook e Instagram las más influyentes; Twitter tiene el menor impacto.

Este estudio compara el fenómeno de la compra impulsiva tanto en el canal físico como online, y explora la influencia de las redes sociales en la compra impulsiva.

This study aims to investigate the factors that influence South African customers to potentially switch from one bank to another. Instead of using established models and survey techniques, the research measured social media sentiment to measure threats to switch.

The research involved a 12-month analysis of social media sentiment, specifically customer threats to switch banks (churn). These threats were then analysed for co-occurring themes to provide data on the reasons customers were making these threats. The study used over 1.7 million social media posts and focused on all five major South African retail banks (essentially the entire sector).

This study concluded that seven factors are most significant in understanding the underlying causes of churn. These are turnaround time, accusations of unethical behaviour, billing or payments, telephonic interactions, branches or stores, fraud or scams and unresponsiveness.

This study is unique in its measurement of unsolicited social media sentiment as opposed to most churn-related research that uses survey- or customer-data-based methods. In addition, this study observed the sentiment of customers from all major retail banks across 12 months. To date, no studies on retail bank churn theory have provided such an extensive perspective. The findings contribute to Susan Keaveney’s churn theory and provide a new measurement of switching threat through social media sentiment analysis.

Despite the abundance of small-scale farms in the USA and their importance for both rural economic development and food availability, the extensive research on small business management and entrepreneurship has mostly neglected the agricultural context, leaving many of these farms' business challenges unexplored. The authors focus on informing a specific decision faced by small farm managers: selling directly to consumers (i.e. farmer's markets) versus selling through aggregators. By collecting historical data and a series of interviews with industry experts, the authors employ simulation methodology to offer a framework that advises how small-scale farmers can allocate their product across these two channels to increase revenue in a given season. The results, which are relevant for operations management, small business management and entrepreneurship literature, can help small-scale farmers improve their performance and compete against their larger counterparts.

The authors rely on historical and interview data from key industry players (an aggregator and a small farm manager) to design a simulation analysis that determines which factors influence season-long farm revenue performance under varying strategies of channel allocation and commodity production.

The model suggests that farm managers should plan to evenly split their production between the two distribution channels, but if an even split is not possible, they should plan to keep a larger percentage in the nonaggregator (farmers' market/direct) channel. Further, the authors find that farmers can benefit significantly from a strong aggregator channel customer base, which suggests that farmers should promote and advertise the aggregator channel even if they only use it for a limited amount of their product.

The authors integrate small business management and operations management literature to study a widely understudied context and present practical implications for the performance of small-scale farms.

The onset of a crisis demands that businesses respond quickly and effectively. So, it might be helpful to examine the effect of business model innovation and how to increase its impact on better crisis management. This study aims to discuss the aforementioned objectives.

The present study is applied in terms of aim and a quantitative descriptive survey regarding the data collection method. The structural equation model with the partial least squares approach and Smart PLS 3 software was used for the structural analysis of the questionnaire.

The findings revealed that business model innovation could lead to better crisis management. In addition, the components of entrepreneurial capability, resilience and business performance played a mediating role.

Some factors may mediate the effect of business model innovation on crisis management. Thus, future research can investigate them and identify their impact.

The present study suggests that managers should re-examine business model processes and make them innovative to improve crisis management.

The present study examines the factors that affect crisis management with an emphasis on innovation, assesses the impact of mediating factors in this regard and attempts to provide a model to facilitate better crisis management.