Search results

Product trials are an effective way to influence consumer attitudes. While research has established several factors that influence whether consumers will try a product or not, it is less understood how marketers can optimize the trial experience itself. The purpose of this paper is to explore flow as an optimal state and the factors that give rise to it during a product trail.

This research consists of three experimental studies in which people trial new music. This paper explores the ability of curiosity to optimize consumers’ flow experience during the trial and their attitudes toward the trialed product. This paper manipulates curiosity before the trial using information about the music (Study 1) and music previews (Study 3) and also demonstrates that curiosity is naturally elevated among those high in openness to experience (Study 2).

The results demonstrate that curiosity before a product trial fosters an optimal experience during the trial in the form of flow states, defined as an enjoyable state of full engagement, which in turn mediates more positive attitudes toward the trialed product. This paper demonstrates that curiosity can be evoked using product information or a preview of the content and can vary based on individual differences in openness to experience. The relationship between curiosity and flow is moderated by the valence of the information that is used to elicit curiosity, such that negative-valence information thwarts the relationship.

While the studies conducted by the authors focus on the positive influence of curiosity in the trial of music, the effects may be different for other products. These studies are also limited to two different manipulations of curiosity.

This research has implications for marketers, as it demonstrates the relevance of flow and how to enable it in product trials to optimize effectiveness. The manipulations also demonstrate how to manage the amount of information that is given to consumers before they trial a product.

This research reveals that flow states optimize the product trial experience. This research also advances the understanding of the relationship between curiosity and flow by moderating their relationship with the valence of information that elicits curiosity. The findings also broaden the relevance of curiosity and flow in marketing by demonstrating their benefits within product trials.

This article considers how digital technologies are informed by, and implicated in, the systematic and interlocking oppressions of colonialism, misogyny, and racism, all of which have been identified as root causes of the missing and murdered Indigenous women crisis in Canada. The authors consider how technology can facilitate multiple forms of violence against women including stalking and intimate partner violence, human trafficking, pornography and child abuse images, and online hate and harassment and note instances where Indigenous women and girls may be particularly vulnerable. The authors also explore some of the complexities related to police use of technology for investigatory purposes, touching on police use of social media and DNA technology. Without simplistically blaming technology, the authors argue that technology interacts with multiple factors in the complex historical, socio-cultural environment that incubates the national crisis of missing and murdered Indigenous women and girls. The article concludes with related questions that may be considered at the impending national inquiry.

This case study examines the new product development (NPD) process of digital information products (DIPs) and its critical success factors (CSFs) in a small-sized German enterprise.

A case study was conducted with a small firm focused on the development of DIPs; data were obtained through semi-structured interviews, direct observation and document analysis.

The firm uses an informal and cross-functional NPD process (idea generation, idea validation, product creation and product launch) in converting an idea into a sellable product. Peculiar aspects of each stage within the process as well as ten CSFs to NPD projects were verified.

Limitations are attributed to its qualitative nature, which does not allow generalizations, though careful attention was given to validity and reliability issues through the use of data source triangulation.

The paper provides a conceptual process that may benefit further initiatives for developing and launching DIPs, as well as a comprehensive list of CSFs for such projects.

This paper is the first one to schematize the NPD process and practices for DIPs, as well as key capabilities. It contributes to the NPD literature in discussing dynamic aspects that are typical to the firm analyzed and to others operating in a digital context. At the same time, it reinforces other traditional aspects that have become overlooked in digital business debates.

Private equity and venture capital (VC) firms in the capital markets sector invest capital with the primary goal of delivering economic value. However, some firms in the capital markets sector have started to shift this focus to create (i.e. invest in) social value. More specifically, traditional VC firms are starting socially oriented funds, while other firms have emerged to focus solely on investments in social enterprises. These VC firms are contributing to an interesting paradox – performance metrics are not measured by profit alone but also by social innovation. From an architectural perspective, the authors examine the implications of internal design, i.e. how specific strategic and structural factors influence the financial performance of VC firms with a social orientation to determine if these firms really can “do well and do good.”

Social orientation was determined by content analysis of mission statements of the VC firms. Firm strategies, structures and performance were sourced from secondary data. A moderated mediation model was used to test relationships.

Results suggest that (1) socially responsible VC firms adopt distinct foci of social investing that directs their strategic orientation and (2) these various foci have vastly differing effects on the firm's overall performance, strategic decisions made and the architecture of their structural design.

This study is among the first to explore socially responsible VC architectural dimensions, with implications for firm design based on blended measures of success.

This study aims to examine the ability of clean energy stocks to provide cover for investors against market risks related to climate change and disturbances in the oil market.

The study adopts the feasible quasi generalized least squares technique to estimate a predictive model based on Westerlund and Narayan’s (2015) approach to evaluating the hedging effectiveness of clean energy stocks. The out-of-sample forecast evaluations of the oil risk-based and climate risk-based clean energy predictive models are explored using Clark and West’s model (2007) and a modified Diebold & Mariano forecast evaluation test for nested and non-nested models, respectively.

The study finds ample evidence that clean energy stocks may hedge against oil market risks. This result is robust to alternative measures of oil risk and holds when applied to data from the COVID-19 pandemic. In contrast, the hedging effectiveness of clean energy against climate risks is limited to 4 of the 6 clean energy indices and restricted to climate risk measured with climate policy uncertainty.

The study contributes to the literature by providing extensive analysis of hedging effectiveness of several clean energy indices (global, the United States (US), Europe and Asia) and sectoral clean energy indices (solar and wind) against oil market and climate risks using various measures of oil risk (WTI (West Texas intermediate) and Brent volatility) and climate risk (climate policy uncertainty and energy and environmental regulation) as predictors. It also conducts forecast evaluations of the clean energy predictive models for nested and non-nested models.

The transaction process of an office building is known to be time consuming and inefficient, in part due to the lack of market transparency. The purpose of this paper is to focus on the development of a blockchain application that can improve the transaction process of office buildings in the Netherlands.

Conducting design science research, the current transaction process of an office building and status quo of blockchain technology in real estate is investigated. Subsequently, multiple parties are interviewed to define major pain points within the process. The interview findings are used to design a blockchain solution which overcomes the aforementioned pain points. After designing, the interviewees are asked again to pragmatically validate the proposed model.

One of the major pain points identified concerning the transaction process of an office building is that it is difficult to define the characteristics of a property, due to lack of data structure and quality. The proposed application improves the way specific assets are understood by structuring physical and contractual information in one place and guarantees the quality of the data by using the blockchain mechanisms.

A blockchain application is proposed, which can improve the transaction process of an office building.

Recent studies indicate that blockchain technology could lead to improvements in efficiency, transparency and therefore trust within the transaction process. Therefore, the proposed application is of value for the future of real estate data management and the transaction process.

This article aims to provide a theoretical unifying framework for flexible organizational forms, such as so-called adhocracies and network organizations.

In this article, organization practices that are typical of the software industry are analyzed and re-interpreted by means of foundational concepts of organization science. It is shown that one and the same logic is at work in all flexible organizations.

Coordination modes can be fruitfully employed to characterize flexible organizations. In particular, standardization is key in order to obtain flexibility, provided that a novel sort of coordination by standardization is added to those that have been conceptualized hitherto.

This article highlights one necessary condition for organizations to be flexible. Further aspects, only cursorily mentioned in this paper, need to be addressed in order to obtain a complete picture.

A theory of organizational flexibility constitutes a guide for organizational design. This article suggests the non-obvious prescription that the boundary conditions of individual behavior must be standardized in order to achieve operational flexibility.

This theoretical framework can be profitably employed in management classes.

Currently, flexible organizations are only understood in terms of lists of instances. This article shows that apparently heterogeneous case-studies share common features in fact.

Loan default risk or credit risk evaluation is important to financial institutions which provide loans to businesses and individuals. Loans carry the risk of being defaulted. To understand the risk levels of credit users (corporations and individuals), credit providers (bankers) normally collect vast amounts of information on borrowers. Statistical predictive analytic techniques can be used to analyse or to determine the risk levels involved in loans. This paper aims to address the question of default prediction of short-term loans for a Tunisian commercial bank.

The authors have used a database of 924 files of credits granted to industrial Tunisian companies by a commercial bank in the years 2003, 2004, 2005 and 2006. The naive Bayesian classifier algorithm was used, and the results show that the good classification rate is of the order of 63.85 per cent. The default probability is explained by the variables measuring working capital, leverage, solvency, profitability and cash flow indicators.

The results of the validation test show that the good classification rate is of the order of 58.66 per cent; nevertheless, the error types I and II remain relatively high at 42.42 and 40.47 per cent, respectively. A receiver operating characteristic curve is plotted to evaluate the performance of the model. The result shows that the area under the curve criterion is of the order of 69 per cent.

The paper highlights the fact that the Tunisian central bank obliged all commercial banks to conduct a survey study to collect qualitative data for better credit notation of the borrowers.

El riesgo de incumplimiento de préstamos o la evaluación del riesgo de crédito es importante para las instituciones financieras que otorgan préstamos a empresas e individuos. Existe el riesgo de que el pago de préstamos no se cumpla. Para entender los niveles de riesgo de los usuarios de crédito (corporaciones e individuos), los proveedores de crédito (banqueros) normalmente recogen gran cantidad de información sobre los prestatarios. Las técnicas analíticas predictivas estadísticas pueden utilizarse para analizar o determinar los niveles de riesgo involucrados en los préstamos. En este artículo abordamos la cuestión de la predicción por defecto de los préstamos a corto plazo para un banco comercial tunecino.

Utilizamos una base de datos de 924 archivos de créditos concedidos a empresas industriales tunecinas por un banco comercial en 2003, 2004, 2005 y 2006. El algoritmo bayesiano de clasificadores se llevó a cabo y los resultados muestran que la tasa de clasificación buena es del orden del 63.85%. La probabilidad de incumplimiento se explica por las variables que miden el capital de trabajo, el apalancamiento, la solvencia, la rentabilidad y los indicadores de flujo de efectivo.

Los resultados de la prueba de validación muestran que la buena tasa de clasificación es del orden de 58.66% ; sin embargo, los errores tipo I y II permanecen relativamente altos, siendo de 42.42% y 40.47%, respectivamente. Se traza una curva ROC para evaluar el rendimiento del modelo. El resultado muestra que el criterio de área bajo curva (AUC, por sus siglas en inglés) es del orden del 69%.

El documento destaca el hecho de que el Banco Central tunecino obligó a todas las entidades del sector llevar a cabo un estudio de encuesta para recopilar datos cualitativos para un mejor registro de crédito de los prestatarios.

Curva ROC, Evaluación de riesgos, Riesgo de incumplimiento, Sector bancario, Algoritmo clasificador bayesiano.

Artículo de investigación

Several e-payment technologies have diffused in Nigeria yet debit card usage on POS devices have not shown consumer confidence in its usage thereby affecting the cashless policy drive of the nation. The study considered an affective commitment of users as moderating their behaviours. Therefore, the purpose of this paper is to investigate how user behaviour is moderated by an affective commitment on point of sale terminal.

Following the purpose of the study, the research design is a survey. The questionnaire was adapted from earlier studies and tested for reliability and validity using Cronbach’s alpha and content validity. Andrew F. Hayes process was used to analyse the moderation effect.

The finding revealed that affective commitment significantly moderates users’ ease of use of the device, their perceived usefulness of the device and their social image on their intentions to use the device.

The findings implied that there is a need for the development of policies and strategies which should be directed towards the users of the device. Equally, the general conclusions on collective e-payment channels in a society should be discarded given that each e-payment channel can have different factors influencing it than the others. This is where customer-focused advertising and awareness campaign becomes very important.

This paper declares that the research work is not submitted anywhere for publication or for review. It was conducted by the authors who have given their consent for it to be submitted to Rajagiri management journal