Intellectual capital efficiency and firm performance: evidence from an emerging knowledge-economy

Akter, Refa; Bhattacharjee, Swadip

doi:10.1504/ijlic.2021.10038760

Cited by 6 publications

(6 citation statements)

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“…In addition, the resource-based view explains the relationship between IC and firm performance in several studies (Bataineh et al, 2022 ; Bhattacharjee & Akter, 2021 ; Ur Rehman et al, 2022 ). Unique resources, whether tangible or intangible, support firm performance (Habib & Kayani, 2022 ; Habib & Mourad, 2022 ).…”

Section: Literature Reviewmentioning

confidence: 99%

Does the Efficiency of a Firm’s Intellectual Capital and Working Capital Management Affect Its Performance?

Habib¹,

Dalwai

2023

J Knowl Econ

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This study explores the efficiency of intellectual capital (ICE) and working capital management (WCME) in the GCC industrial sector and its potential impact on firm performance. The data were gathered from Standard & Poor’s database from 2015 to 2019. This study uses data envelopment analysis (DEA), regression analysis, and robustness tests to accomplish its aims. The results indicate that most firms do not employ their intellectual and working capital investments well and need improvement actions to achieve the best practices. The regression model results reveal that ICE and WCME significantly and positively influence firms’ performance. The results of this study support the resource-based, trade-off, and pecking order theories. The study findings have important implications for many stakeholders; for example, they would be helpful for firm decision-makers in managing their investments in intellectual and working capital to achieve the best practices and improve a firm's performance. In addition, the findings would be helpful for financiers, because high-performance firms are likely to have more reasonable valuations that facilitate debt financing. Moreover, the findings have noteworthy implications for trading procedures as investors aspire to attractive economic returns for their investments in corporations that pasture ICE and WCME issues. Additionally, these findings have important implications for employee job satisfaction and retention by improving IC management.

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Section: Literature Reviewmentioning

confidence: 99%

Does the Efficiency of a Firm’s Intellectual Capital and Working Capital Management Affect Its Performance?

Habib¹,

Dalwai

2023

J Knowl Econ

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“…Bangladesh is on the way to becoming the South Asian knowledge hub [ 12 ] having been transformed from a labor-intensive to a knowledge-intensive economy. The banking sector leads the country as the financier of virtually all sorts of industrial activities.…”

Section: Literature Review and Hypotheses Developmentmentioning

confidence: 99%

“…Among the three dimensions of competitive advantages such as differentiation, outreach level, and cost leadership strategy [ 68 ], IC harnesses more on the differentiation strategy [ 62 ]. Achieving competitive advantages in effect ensures boosted firm performance [ 12 , 69 ].…”

Section: Literature Review and Hypotheses Developmentmentioning

confidence: 99%

“…After reviewing various recent works on the relationship between IC and firm performance, we have found several research gaps to address. First of all, most of the studies use the controversial VAIC model while representing IC [ [12] , [13] , [14] , [15] , [16] , [17] ]. Then, the use of corporate governance variables as controls has long been ignored and incomplete.…”

Section: Introductionmentioning

confidence: 99%

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Does intellectual capital drive bank's performance in Bangladesh? Evidence from static and dynamic approach

Faruq

Akter

Rahman

2023

Heliyon

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“…The model's inclusion of experience as a crucial determinant of compensation outcomes is expected to serve as a powerful source of motivation for employees, as EXT emphasizes the importance of equitable compensation decisions that accurately reflect an employee's contributions, resulting in improved job performance and heightened levels of motivation and satisfaction. Furthermore, it can be confidently posited that the proposed model, which regards education as an essential predictor variable, impeccably aligns with the fundamental tenets of the HCT and effectively recognizes and incentivizes human capital investment, thereby promoting the development of employees' skills and competencies (Bhattacharjee and Akter, 2022). Consequently, the model's steadfast adherence to the HCT is expected to engender various salutary outcomes, such as heightened employee performance, augmented job satisfaction and improved organizational productivity (Grimpe et al.…”

Section: Discussionmentioning

confidence: 99%

Dissecting the compensation conundrum: a machine learning-based prognostication of key determinants in a complex labor market

Jaiswal

Gupta²,

Tiwari

2023

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PurposeAmidst the turbulent tides of geopolitical uncertainty and pandemic-induced economic disruptions, the information technology industry grapples with alarming attrition and aggravating talent gaps, spurring a surge in demand for specialized digital proficiencies. Leveraging this imperative, firms seek to attract and retain top-tier talent through generous compensation packages. This study introduces a holistic, integrated theoretical framework integrating machine learning models to develop a compensation model, interrogating the multifaceted factors that shape pay determination.Design/methodology/approachDrawing upon a stratified sample of 2488 observations, this study determines whether compensation can be accurately predicted via constructs derived from the integrated theoretical framework, employing various cutting-edge machine learning models. This study culminates in discovering a random forest model, exhibiting 99.6% accuracy and 0.08° mean absolute error, following a series of comprehensive robustness checks.FindingsThe empirical findings of this study have revealed critical determinants of compensation, including but not limited to experience level, educational background, and specialized skill-set. The research also elucidates that gender does not play a role in pay disparity, while company size and type hold no consequential sway over individual compensation determination.Practical implicationsThe research underscores the importance of equitable compensation to foster technological innovation and encourage the retention of top talent, emphasizing the significance of human capital. Furthermore, the model presented in this study empowers individuals to negotiate their compensation more effectively and supports enterprises in crafting targeted compensation strategies, thereby facilitating sustainable economic growth and helping to attain various Sustainable Development Goals.Originality/valueThe cardinal contribution of this research lies in the inception of an inclusive theoretical framework that persuasively explicates the intricacies of a machine learning-driven remuneration model, ennobled by the synthesis of diverse management theories to capture the complexity of compensation determination. However, the generalizability of the findings to other sectors is constrained as this study is exclusively limited to the IT sector.

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Intellectual capital efficiency and firm performance: evidence from an emerging knowledge-economy

Cited by 6 publications

References 0 publications

Does the Efficiency of a Firm’s Intellectual Capital and Working Capital Management Affect Its Performance?

Does the Efficiency of a Firm’s Intellectual Capital and Working Capital Management Affect Its Performance?

Does intellectual capital drive bank's performance in Bangladesh? Evidence from static and dynamic approach

Dissecting the compensation conundrum: a machine learning-based prognostication of key determinants in a complex labor market

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