Disclosure of Strategic Managers’ Factotum: Behavioral Incentives of Innovative Business

Ďurana, Pavol; Valášková, Katarína; Vagner, Ladislav; Zadnanova, Silvia; Podhorská, Ivana; Siekelová, Anna

doi:10.3390/ijfs8010017

Cited by 40 publications

(46 citation statements)

References 119 publications

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“…Measuring the loyalty level of its customers guides the companies for providing better and exceptional services. If these services are equipped with innovative ideas it may lead toward sustainable growth which ultimately contribute in the innovative ecosystem [30,67]. It was done through users' loyalty and marketing management where marketing engagement was further subdivided into innovative, functional, emotional, and communal engagement.…”

Section: Discussionmentioning

confidence: 99%

“…In fact, innovation plays an intermediary role among the firms' functional deliverables and its overall performance. The outcome of this innovation is enhanced earnings for the business [30]. According to Sawhney, et al [31], Internet or social media has developed a new type of innovation which is known as collaborative innovation.…”

Section: Innovative Engagementmentioning

confidence: 99%

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Innovative Perspective of Marketing Engagement: Enhancing Users’ Loyalty in Social Media through Blogging

Sajjad

Zaman

2020

Journal of Open Innovation: Technology, Market, and Complexity

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The breakneck pace of digital technologies has created a dramatic shift in marketing campaigns to engage users through unique and innovative experiences. Focusing on the same grounds, this study relates the market engagement with users’ loyalty (UL) for Facebook social media. Market engagement has been measured through four constructs of innovative engagement (IE), functional engagement (FE), emotional engagement (EE), and communal engagement (CE). Blogging has been included as a moderator in the relation between IE, FE, EE, CE, and UL. To measure these relationships, study proposed two models and developed five hypotheses. Data were collected through structured questionnaire aimed at referral groups i.e., habitual users of Facebook. A total of 309 responses were included in the analysis through purposive sampling. Model 1 was tested with simple regression and it was found that the overall model was statistically significant and explained 65 percent of variation in UL. It was concluded that for online users, loyalty is affected by IE, FE, and CE, while EE is of least concern for them. Model 2 was tested through hierarchical regression after the inclusion of a moderator of BE in model 1. It was concluded that blogging acted as a partial moderator in between the relationship of IE, FE, EE, CE, and UL as the proposed model 2 was found to be significant. However, only CE yielded significant relationship with UL while IE, FE, and EE yielded insignificant relationship with UL in the presence of a moderator. The study concedes new insights for those social platforms and marketing companies that are seeking innovative and unique ways to retain their online users for long time.

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Section: Discussionmentioning

confidence: 99%

Section: Innovative Engagementmentioning

confidence: 99%

Innovative Perspective of Marketing Engagement: Enhancing Users’ Loyalty in Social Media through Blogging

Sajjad

Zaman

2020

Journal of Open Innovation: Technology, Market, and Complexity

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“…Considering that over 44% of South Korea's gross domestic product (GDP) has relied on exports since 2000, productivity enhancement from exports is pivotal for income growth, which can raise South Korean living standards in the long term. The significant learning gained through exporting signals that the government should efficiently and effectively implement policies designed to support firms' export participation, as well as export-promotion services aimed at reducing information asymmetry and the fixed costs linked to exporting (e.g., training in the export process, specific information services for foreign markets, participation in international fairs, and export promotion programs), especially for non-exporting firms and less-mature exporting firms [76,77]. Our study reveals the underlying mechanisms of benefits gained from exports, indicating that TFP can be augmented by interacting with exports and knowledge assets.…”

Section: Discussionmentioning

confidence: 99%

“…A more industry-dynamic, competitive setting calls for faster, more systematic, and successful responses to such opportunities and threats. A competitive atmosphere requires firms to create novel innovative products and services to succeed [77]. Thus, when industry competition is fierce, companies actively promote organizational learning by better utilizing market-focused knowledge to stay ahead of competitors and survive in the fiercely competitive milieu.…”

Section: Discussionmentioning

confidence: 99%

How Knowledge Assets Affect the Learning-by-Exporting Effect: Evidence Using Panel Data for Manufacturing Firms

Kim

Sung

2020

Sustainability

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Using panel data from Korean manufacturing firms, this study empirically investigates how knowledge assets impact the relationship between exports and productivity. We consider a scenario in which firms are situated in a globally competitive, knowledge-based environment. We establish a dynamic panel vector autoregressive model by considering the outcomes of various panel framework tests. A generalized method of moments estimator is employed to test the dynamic relationships among the variables, and a post-estimation test, Granger causality test, and impulse response test are performed. Our findings indicate the existence of a learning-by-exporting effect on the enhancement of total factor productivity (TFP). The result show that TFP can be improved by interacting with exports and knowledge assets, and that firms’ knowledge assets significantly and positively affect their exports. However, industry competition, as an external force, does not contribute to boosting firms’ productivity. We highlight the importance of continuously upgrading productivity, exports, knowledge assets, and industry competition by demonstrating that the present levels of these elements serve as the main source of their own future values. Finally, the implications of our results are outlined.

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“…This issue is addressed, e.g. by the studies of (Durana et al, 2020;Kovalova & Frajtova Michalikova, 2020;Papik & Papikova, 2020;Podhorska et al, 2019;Svabova et al, 2020;. We dare say that a detection model of earnings manipulation which would accept specifics of the Slovak business environment has not yet been created in Slovakia.…”

Section: Literature Reviewmentioning

confidence: 99%

Detecting earnings manipulation and fraudulent financial reporting in Slovakia

Švábová

Kramárová

Chutka

et al. 2020

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Research background: Misleading financial reporting has a negative impact on all stakeholders since financial records are the primary source of information on financial stability, economic activity, and financial health of any company. The handling of them is primarily the responsibility of managers or owners and reasons for doing so may differ. Their common denominator is the artificial creation of information asymmetry to get different types of benefits. It is, therefore, logical that the issue of detecting opportunistic earnings management comes to the fore. Purpose of the article: The purpose of the study is to create a discriminant model of the detection of earnings manipulators in the conditions of the Slovak economy. Methods: We used the discriminant analysis to create a model to identify fraudulent companies, based on the real data on companies that were convicted from misleading financial reporting in connection with tax fraud in the years 2009–2018. The model is inspired by the Beneish model, which is one of the most applied fraud detection methods at all. Findings & Value added: In order to achieve more accurate detection results, we extended the original model by taking into account the values of indicators from three consecutive years, i.e. by taking into account the development of the potential tendency of companies to be involved in opportunistic earnings management. Our model correctly identified 86.4% of fraudulent companies and overall reaches 84.1% classification ability. Both models were applied on empirical data on 1,900 Slovak companies from the years 2016–2018, while their overlap was 32.7% for fraudulent companies and 38.4% for non-fraud companies. This is a very useful result, as the application of both models rein-forces the results obtained and the identical classification of the company into fraudulent indicates that the manipulation of earnings occurs with a high probability.

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Disclosure of Strategic Managers’ Factotum: Behavioral Incentives of Innovative Business

Cited by 40 publications

References 119 publications

Innovative Perspective of Marketing Engagement: Enhancing Users’ Loyalty in Social Media through Blogging

Innovative Perspective of Marketing Engagement: Enhancing Users’ Loyalty in Social Media through Blogging

How Knowledge Assets Affect the Learning-by-Exporting Effect: Evidence Using Panel Data for Manufacturing Firms

Detecting earnings manipulation and fraudulent financial reporting in Slovakia

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