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Contrary to its highest R&D intensity, Japan has dramatically decreased its productivity in the 1990s. This can be attributed to a low marginal productivity of technology. Such a productivity decrease compels a delay in R&D, which results in reduced R&D productivity leading to a vicious cycle between R&D and its return. In this context optimal timing of R&D is crucial, particularly during economic stagnation and consequent difficulties in financing R&D. This paper analyzes the rationale for optimal timing of R&D and its interacting relationship with marginal productivity of technology. Empirical analyses are attempted focusing on Japan’s leading high‐technology firms and their innovative products.

Purpose: Sustainable functionality development (FD) is decisive to firm's profitability in their new innovation in a competitive market. While functionality instills attractive values in innovative goods leading to a dramatic increase in profit through increasing demand and higher prices, it obsolesces immediately in a competitive market. Therefore, how to maintain sustainable FD trajectory is decisive to firm survival strategy within the context of mega‐competition in a globalizing economy. Notwithstanding an increasing significance of this subject, dynamism enabling a sustainable FD trajectory still remains inside a black box. The purpose of this paper, on the basis of an empirical comparative analysis of the diffusion trajectories for copying machines developed by Canon and Ricoh, is to attempt to elucidate this dynamism. Design/methodology/approach: This paper employed a bi‐logistic growth model utilizing patent data for copying machine technologies. Findings: It was found that early undertaking of 2nd generational copying machinery initiated by Canon played a more decisive role in terms of its higher level of sustainable FD than with its competitor. Originality/value: This paper provides significant insight to firm's management of technology strategy in a competitive market.

A virtuous cycle between effective utilization of external resources and functionality development can be constructed. Given that the timely emergence of new functionality in an efficient way is crucial to a firm's competitive strategy in an era of mega‐competition, construction of such a virtuous cycle is a key element with regard to a firm's technopreneurial strategy. The purpose of this paper is to identify a trigger for such a virtuous cycle.

Empirical comparative analysis taking copying machines development trajectories in Canon and Ricoh and the patent data analysis were conducted.

Cumulative learning from preceding relevant technology development is found to stimulate intra‐technology spillover. Timely intra‐technology spillover from preceding innovation plays a triggering role.

Attempting a broad and comprehensive learning exercise should be strongly encouraged for the effective utilization of external resources for innovation. Fruitful effects of learning should be pursued to the hybrid management of technology fusing indigenous strength and the effects of the comprehensive learning.

Aiming at identifying the trigger emerging a virtuous cycle between effective utilization of external resources and functionality development, core technologies instilled in the copying machines just short of the emergence of functionality development were investigated. In order to anticipate thorough capturing of all dimensions of color technologies utilized for the emergence of new functionality development through indigenous development as well as utilization of externally developed technologies, F‐term retrieval of patent registration data was attempted.

The purpose of this paper is to empirically study the impact of product patent regime on the productivity of different categories such as ownership, R&D, size and product-wise of Indian pharmaceutical firms using non-parametric data envelopment analysis.

The present study has applied Ray and Desli’s Malmquist productivity index and its decomposition to measure total factor productivity (TFP) change, pure technical efficiency change, scale efficiency change and technical change under variable returns to scale (VRS) technology assumption for 141 Indian pharmaceutical firms during 2000-2001 to 2014-2015.

The study found the negligible impact of product patent regime on productivity. The technological change has played a positive role in the growth of productivity, whereas technical efficiency change depicts the judicious utilization of resources for improving performance. From the results, it is found that R&D intensive firms depict better stability in the TFP than the non-R&D firms. However, Granger causality between R&D and productivity found no relationship. Productivity is more directly affected by investment in fixed assets rather than in R&D, which focusses on incremental value additions in a largely branded/plain generic product market. In case of ownership, private foreign firms found to have registered progress in TFP while others have recorded marginal regress, which probably could be attributed to the superior marketing and management skills of the foreign firms, besides possessing proprietary technology. Both small and large firms have shown positive growth in the new regime as compared to the pre-patent regime. These small firms are able to compete with large firms because of their up-gradation of the technological base by improving access to better foreign technology. TFP growth for all the firms can be attributed to improvement in technology, and innovation in terms of high capital-output ratio. Further, the paper tried to identify the determinants of productivity from panel random effect regression, and it is found that export intensity, age and the new patent regime have negative and significant relationship with productivity, whereas other variables such as R&D, ownership, size and capital imports are insignificant. In the end, the results of sensitivity analysis have confirmed the validity of the selected variables.

The results suggest that Indian pharmaceutical firms need substantive improvement in TFP by improving managerial and scale efficiency. Indian pharmaceutical industry (IPI) needs to improve productivity across the network and drive cost excellence initiatives across the spend base through operational excellence and digital initiatives. The results of this paper can be applied in framing policies for future growth and improvement in the productivity of IPI.

The paper aims to make several new contributions to the existing literature. Most of the research papers only analysed TFP of the industry as a whole and detailed firm-wise analysis is needed to capture the true impact at a unit level. This study has analysed the impact of different categories such as ownership, R&D, size and product-wise, and determinants of productivity. The study has used a broader time period and larger panel data to predict the better picture.

The purpose of this study is to explore and evaluate potential nonmonotonicity in the determinants of profit efficiency, specifically IT and R&D investments in the Indian commercial banking sector.

The study employs an alternative stochastic profit efficiency framework and introduces nonmonotonic effects by parameterizing the location and scale parameters of the inefficiency component on an unbalanced panel data set of 72 commercial banks in the 2008–2019 period. Marginal effects across quartiles are calculated using a bias-corrected and accelerated bootstrap procedure of 500 simulations. The study disaggregates across ownership and size for gauging the impact of structure on the associations between determinants of profit efficiency.

The study partially rejects the productivity paradox as it discovers a negative association of IT and R&D with profit inefficiency. However, the observed nonmonotonicity of IT is of significance for bank managers, as the study concludes that overinvestment in IT is detrimental to a bank’s profit-maximizing interests. Further, bank size, loan default and credit risk depict a nonmonotonic relationship across the sample with large banks, high NPAs and high credit risk associated with reducing profit efficiency. In addition, higher margins and greater diversification are related positively to efficiency, and banks with cost-heavy structures or having high liquidity risk associated negatively with efficiency.

To the best knowledge of the authors, the study is perhaps the first to acknowledge and incorporate nonmonotonic associations of IT investments amidst other exogenous determinants under a stochastic profit efficiency framework.

This research estimates a multi-product flexible cost function of airport variable costs. Data for the analysis are a panel of 50 airports from 1996 to 2008. Output includes domestic and international departures, non-aeronautical operating revenues, and the number of transport workload units, where a workload unit is a passenger or the equivalent of a 220 pound packet of cargo. The quasi-fixed factor is the equivalent number of 10,000′ × 150′ runways at an airport. After correcting for first-order serial correlation, the analysis finds that airports operate under constant returns to runway utilization and multi-product decreasing returns to scale, production technology is consistent with product specific returns to capacity utilization and anti-complementarity across outputs, and general airport operations have input substitution possibilities with personnel and contractual repair/maintenance inputs. The study also finds 1.05% technology progress over the sample period, due to strong growth prior to 2001, with similar productivity growth rates for large and medium hubs.

Aim of the present monograph is the economic analysis of the role of MNEs regarding globalisation and digital economy and in parallel there is a reference and examination of some legal aspects concerning MNEs, cyberspace and e‐commerce as the means of expression of the digital economy. The whole effort of the author is focused on the examination of various aspects of MNEs and their impact upon globalisation and vice versa and how and if we are moving towards a global digital economy.

This work examines the impact of institutional agricultural credit on crop productivity of some major crops such as paddy, cotton, wheat and pulses for small and marginal farmers across various social groups.

The cross-sectional field data on socio economic variables was collected from three Indian states from about 400 small and marginal farmers across various social groups using multi-stage stratified random and purposive sampling through a structured questionnaire by interviewing. The method of propensity score matching (PSM) was employed to calculate average treatment effect (ATE) and average treatment effect on the treated (ATET) by categorising sample farmers as treatment group and control group where crop productivity was considered as outcome variable and access to institutional credit was considered as treatment variable.

The PSM estimates reveal that ATE and ATET for all the selected crops are found to be significantly higher for the treated group vis-à-vis non-treated group suggesting that institutional agricultural credit has a statistically and significant positive impact on the crop productivity.

Similar study can be extended for more crops and across regions in India for a universal coverage.

The agricultural credit policy of India has been to increase the access and availability of institutional farm credit. This has led to in general increase in the flow of formal farm credit to agricultural sector. However, the impact of institutional credit and crop productivity especially for small and marginal farmers across social groups is not well recognized in India using field data. Accordingly, this field data study contributes to the existing research by providing fresh evidence from field across social groups for both kharif and rabi crops using recent survey data from small and marginal farmers which has important policy implications.

Systemic industries comprise groups of firms making component products that are valued as complements by consumers (PC, automobiles, aircraft, networking). In this study, we investigate the distribution of research effort across the technological system by individual firms as a basis for building competitive advantage. Our empirical setting is a sample of component makers in the personal computer system. We show that even in a sample dominated by focused component manufacturers, diversified research effort in the broader technological system improves R&D productivity in the component technology. Broad scope R&D in the rest of the system also increases the marginal benefits of research efforts in the component technology, though at a diminishing rate. We explore the determinants of this complementarity between the scope of system level research and the focus on component level research, and derive implications for competitive advantage.

Wages have been spreading out across workers over time – or in other words, the 90th/50th wage ratio has risen over time. A key question is, has the productivity distribution also spread out across worker skill levels over time? Using our calculations of productivity by skill level for the United States, we show that the distributions of both wages and productivity have spread out over time, as the right tail lengthens for both. We add Organization for Economic Co-Operation and Development (OECD) countries, showing that the wage–productivity correlation exists, such that gains in aggregate productivity, or GDP per person, have resulted in higher wages for workers at the top and bottom of the wage distribution. However, across countries, those workers in the upper-income ranks have seen their wages rise the most over time. The most likely international factor explaining these wage increases is the skill-biased technological change of the digital revolution. The new artificial intelligence (AI) revolution that has just begun seems to be having similar skill-biased effects on wages. But this current AI, called “supervised learning,” is relatively similar to past technological change. The AI of the distant future will be “unsupervised learning,” and it could eventually have an effect on the jobs of the most highly skilled.