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Big data marketing analytics (BDMA) has been discovered to be a key contributing factor to developing necessary marketing capabilities. This research aims to investigate the impact of the technology and information quality of BDMA on the critical marketing capabilities by differentiating between firms with low and high perceived market performance.

The responses were collected from marketing professionals familiar with BDMA in North America (N = 236). The analysis was done with partial least squares-structural equation modelling (PLS-SEM).

The results indicated positive and significant relationships between the information and technology quality as exogenous constructs and the endogenous constructs of the marketing capabilities of marketing planning, implementation and customer relationship management (CRM) with mainly moderate effect sizes. Differences in the path coefficients in the structural model were detected between firms with low and high perceived market performance.

This research indicates the critical role of technology and information quality in developing marketing capabilities. The study discovered heterogeneity in the sample population when using the low and high perceived market performance as the source of potential heterogeneity, the presence of which would likely cause a threat to the validity of the results in case heterogeneity is not considered. Thus, this research builds on previous research by considering this issue.

This study aims at proposing and testing a model delineating how and when the quality of a special B2B professional service, investment relations (IR), would drive corporate intangible value.

This study employs a proprietary dataset on voting records of an annual investment relations (IR) awards event and the corresponding company-level archival data for analysis. Regression analysis is used to test hypotheses.

IR service quality not only directly enhances corporate intangible value, but also indirectly boosts it via information transparency. While competitive intensity does not moderate the relationship between IR service quality and corporate intangible value, its moderating effect on the relationship between information transparency and this value is negative.

The findings advance academic understanding of the mechanism and boundary conditions underlying the complex and dynamic relationships among IR service quality, information transparency, corporate intangible value and competitive intensity. Future research endeavors to verify the present findings in other service and/or geographic settings would help establish their external validity.

The findings advise companies to expand the traditional role of IR by taking it as a powerful communication and relationship marketing tool to improve their visibility and attract investors.

The findings suggest that superior IR service would strengthen the company’s social bonding with institutional investors and effectively signal to them its commitment to good corporate governance practices.

Matching a proprietary dataset on IR voting records with the corresponding company-level archival data over a five-year period to investigate the performance implications of IR service quality within the Hong Kong context rectifies methodological limitation and geographic confinement of prior IR research.

This paper deals with external audits, which are now commonly used in many industries (e.g. food, automotive and electrical). This study aims to assess whether a given organization meets the specific criteria. If the audit ends with a positive result, information about it is provided to selected interested parties, e.g. clients or contractors. Credibility is pivotal in adding value for all interested parties within the audit processes. This study seeks the factors which, in the opinion of the audited enterprises, have the most decisive impact on the credibility of external audits.

In keeping with the extant literature, research questions were developed regarding the factors influencing the credibility assessment of external audits. Data collected from 100 companies in the Polish food sector were used to construct the model and carry out statistical analyses. Linear regression analyses were also applied to determine the key factors influencing the credibility of audits.

This study is part of the research trend on the rationality of external audits and certification of quality management systems. This paper identifies nine main factors shaping the credibility of external audits. Two of them have the most decisive influence on credibility. The first one is the professional audit method (procedure). The second factor is the auditor’s knowledge of the specificity of the audited area.

This study did not consider the impact that the image/credibility of the organization represented by the auditors may have on the reliability of audits. This is one of the fundamental limitations that should be considered when analyzing the obtained results. To recognize this type of dependence, additional research should be carried out. Another limitation is that the research covers the food industry only. It would be interesting to know the situation in other types of industries.

This paper looks at the possibility of increasing the added value for audited enterprises. The proposed model can be used by managers of organizations conducting external audits and auditors to effectively use resources for process improvement, influencing the maximization of credibility of activities in the area of conformity assessment.

The originality of this study lies in adopting the perspective of audited enterprises in assessing the credibility of audits. To the best of the authors’ knowledge, this is the first study that adopts this approach. This paper contributes to the literature, particularly to better understand audited enterprises’ behavior (trust in audit results, satisfaction with audits, etc.).

The credit of agricultural product quality and safety reflects the ability of the main actors involved in the supply chain to provide reliable agricultural products to consumers. To fundamentally solve the problem of agricultural product quality and safety, it is worth studying how to make the credit awareness and integrity self-discipline of the supply chain agriculture-related subjects strengthened and the role and value of credit supervision given full play. Starting from the application of blockchain in the agricultural product supply chain, this paper aims to investigate the main factors affecting the credit regulation of agricultural product quality.

Using the DEMATEL-ISM (decision-making trial and evaluation laboratory–interpretative structural modeling) method, we analyze the credit influencing factors of agricultural quality and safety empowered by blockchain technology, find the causal relationship between the crucial influencing factors and deeply explore the hierarchical transmission relationship between the influencing factors. Then, the path analysis in structural equation modeling is utilized to verify and measure the significance and effect value of the transmission relationship among the crucial influencing factors of credit regulation.

The results show that the quality and safety credit regulation of agricultural products is influenced by a combination of direct and deep influencing factors. Long-term stable cooperative relationship, Quality and safety credit evaluation, Supply chain risk control ability, Quality and safety testing, Constraints of the smart contract are the main influence path of blockchain embedded in agricultural product supply chain quality and safety credit supervision.

Credit supervision is an important means to improve the ability and level of social governance and standardize the market order. From the perspective of blockchain embedded in the agricultural supply chain, the regulatory body is transformed from the product body to the supply chain body. Take the credit supervision of supply chain subjects as the basis of agricultural product quality supervision. With the help of blockchain technology to improve the effectiveness of agricultural product quality and safety credit supervision, credit supervision is used to constrain and incentivize the behavior of agricultural subjects.

Lack of appropriate student support and drawbacks in academic progression signify the importance of enhancing assessment and feedback in higher education (HE). Although assessment and feedback are significant in HE, minimal empirical research holistically explores the best practices. This study aims to address the niche and develop a decisive guideline for enhancing assessment setting and feedback provision within HE curricula.

A systematic approach was taken to obtain data for the study: a literature review underpinning the thematic content analysis of study documents, followed by semi-structured interviews. Document analysis contained mid-module reviews/student feedback; rubrics used in assessment; and formative/summative feedback provided for the graded work. Documental analysis informed the key attributes of the semi-structured interview. Interpretive structural modelling (ISM) analysis identified the influence and reliance of each driver.

This study revealed 15 drivers – 4 fundamental, 6 significant and 5 important – for enhancing assessment and feedback. The level partitioning from the ISM analysis established that all assessment and feedback needs to be underpinned by the university policy and fed into the assessment regime and marking scheme. This study identified that National Student Survey results were significantly improved due to implementing said drivers compared with the national and sector benchmarks.

The developed drivers enable the best practices in assessment setting and feedback provision. The level partition diagram can be used as a decisive guideline or a provisional framework in assessment and feedback provision for quality assurance in HE.

This study is one of, if not the only, to develop a guideline for signposting drivers and their influence and reliance to enhance assessment and feedback in a holistic HE setting. The developed drivers and the level partition diagram bring novelty and add to the current body of knowledge.

The authors examine the role of CEO political ideology in the credit rating process.

This study adopts a quantitative method with panel data regressions using a sample of 5,211 observations from S&P 500 firms from 2001 to 2012.

The authors find that firms run by Republican-leaning CEOs, who tend to have conservative political ideologies, enjoy more favorable credit ratings than firms run by Democratic-leaning CEOs. In addition, the association between CEO political ideology and credit ratings is more pronounced for firms with high operating uncertainty, low capital intensity, high growth potential, weak corporate governance and low financial reporting quality. Finally, the authors find that CEO political ideology affects a firm's cost of debt incremental to credit ratings, consistent with debt investors incorporating CEO political ideology in their pricing decisions.

Leveraging CEO political ideology, the authors document that credit rating agencies incorporate managerial conservatism in their credit rating decisions. This finding suggests that CEO political ideology serves as a meaningful signal for managerial conservatism.

The study suggests that credit rating agencies incorporate CEO political ideology in their credit rating process. Other capital market participants such as auditors and retail investors can also use CEO political ideology as a proxy for managerial conservatism when evaluating firms.

The paper carries practical implications for practitioners, firm executives and regulators. The results on the association between CEO political ideology and credit ratings suggest that other financial institutions could also incorporate CEO political ideology in their evaluation in their evaluation of firms. For example, when evaluating audit risk and determining audit pricing, auditors may add CEO political ideology as a risk factor. For firms, especially those that have Democratic-leaning CEOs, the authors suggest that they could reduce the unfavorable effect of CEO political ideology on credit ratings by improving their corporate governance and financial reporting quality, as demonstrated in the cross-sectional analyses. Finally, this study shows that CEO political ideology, as measured by CEOs' political contributions, is closely related to a firm's credit ratings. This finding may inform regulators that greater transparency for CEOs' political contributions is needed as information on contributions could help capital market participants perform risk analyses for firms.

Credit rating agencies release their research methodologies for determining corporate credit ratings and identify managerial conservatism as an important factor that affects their risk assessments. The extant literature, however, has not empirically investigated the relation between credit ratings and managerial conservatism, which, according to behavioral consistency theory, can be proxied by CEO political ideology. This study provides novel empirical evidence that identifies CEO political ideology as an important input factor in the credit rating process.

This paper aims to investigate how congruent keywords are used in information security policies (ISPs) to pinpoint and guide clear actionable advice and suggest a metric for measuring the quality of keyword use in ISPs.

A qualitative content analysis of 15 ISPs from public agencies in Sweden was conducted with the aid of Orange Data Mining Software. The authors extracted 890 sentences from these ISPs that included one or more of the analyzed keywords. These sentences were analyzed using the new metric – keyword loss of specificity – to assess to what extent the selected keywords were used for pinpointing and guiding actionable advice. Thus, the authors classified the extracted sentences as either actionable advice or other information, depending on the type of information conveyed.

The results show a significant keyword loss of specificity in relation to pieces of actionable advice in ISPs provided by Swedish public agencies. About two-thirds of the sentences in which the analyzed keywords were used focused on information other than actionable advice. Such dual use of keywords reduces the possibility of pinpointing and communicating clear, actionable advice.

The suggested metric provides a means to assess the quality of how keywords are used in ISPs for different purposes. The results show that more research is needed on how keywords are used in ISPs.

The authors recommended that ISP designers exercise caution when using keywords in ISPs and maintain coherency in their use of keywords. ISP designers can use the suggested metrics to assess the quality of actionable advice in their ISPs.

The keyword loss of specificity metric adds to the few quantitative metrics available to assess ISP quality. To the best of the authors’ knowledge, applying this metric is a first attempt to measure the quality of actionable advice in ISPs.

Business intelligence (BI) systems and tools are deemed to be a transformative source with the potential to contribute to reshaping the way different healthcare organizations’ (HCOs) services are offered and managed. However, this emerging field of research still appears underdeveloped and fragmented. Hence, this paper aims to reconciling, analyzing and synthesizing different strands of managerial-oriented literature on BI in HCOs and to enhance both theoretical and applied future contributions.

A literature-based framework was developed to establish and guide a three-stage state-of-the-art systematic literature review (SLR). The SLR was undertaken adopting a hybrid methodology that combines a bibliometric and a content analysis.

In total, 34 peer-review articles were included. Results revealed significant heterogeneity in theoretical basis and methodological strategies. Nonetheless, the knowledge structure of this research’s stream seems to be primarily composed of five clusters of interconnected topics: (1) decision-making, relevant capabilities and value creation; (2) user satisfaction and quality; (3) process management, organizational change and financial effectiveness; (4) decision-support information, dashboard and key performance indicators; and (5) performance management and organizational effectiveness.

To the authors’ knowledge, this is the first SLR providing a business and management-related state-of-the-art on the topic. Besides, the paper offers an original framework disentangling future research directions from each emerged cluster into issues pertaining to BI implementation, utilization and impact in HCOs. The paper also discusses the need of future contributions to explore possible integrations of BI with emerging data-driven technologies (e.g. artificial intelligence) in HCOs, as the role of BI in addressing sustainability challenges.