Strategic drivers for product and process innovation

Scenarios for optimizing timing for new product exits: a trifecta of models' predictive performances

Purpose

The purpose of the study is applying and comparing models that predict optimal time for new product exit based on its demand pattern and survivability. This is to decide whether or not to continue investing in new product development (NPD).

Design/methodology/approach

The study investigates the optimal time for new product exit within the hi-tech sector by applying three models: the dynamic learning demand model (DLDM), the generalized Bass model (GBM) and the hazard model (HM). Further, for inter- and intra-model comparison, the authors conducted a simulation, considering Weiner and exponential price functions to enhance generalizability.

Findings

While higher price volatility signifies an unstable technology, greater investment into research and development (R&D) and marketing results in higher product adoption rates. Imitators have a more prominent role than innovators in determining the longevity of hi-tech products.

Originality/value

The study conducts a comparison of three different models considering time-varying parameters. There are four scenarios, considering variations in advertising intensity and content, word-of-mouth (WOM) effect, price volatility effect and sunk cost effect.

Benchmarking smart manufacturing drivers using Grey TOPSIS and COPRAS-G approaches

Purpose

The objective of the study is to identify and analyse drivers of smart manufacturing using integrated grey-based approaches. The analysis facilitates industry practitioners in the identification of preference of drivers through which smart manufacturing can be implemented. These drivers are explored based on existing literature and expert opinion.

Design/methodology/approach

Modern manufacturing firms have been adopting smart manufacturing concepts to sustain in the global competitive landscape. Smart manufacturing incorporates integrated technologies with a flexible workforce to interlink the cyber and physical world. In order to facilitate the effective deployment of smart manufacturing, key drivers need to be analysed. This article presents a study in which 25 drivers of smart manufacturing and 8 criteria are analysed. Integrated grey Technique for Order Preference by Similarity to Ideal Solution (grey TOPSIS) is applied to rank the drivers. The derived ranking is validated using “Complex Proportional Assessment – Grey” (COPRAS-G) approach.

Findings

In total, 25 drivers with 8 criteria are being considered and an integrated grey TOPSIS approach is applied. The ranking order of drivers is obtained and further sensitivity analysis is also done.

Research limitations/implications

In the present study, 25 drivers of smart manufacturing are analysed. In the future, additional drivers could be considered.

Practical implications

The study presented has been done with inputs from industry experts, and hence the inferences have practical relevance. Industry practitioners need to focus on these drivers in order to implement smart manufacturing in industry.

Originality/value

The analysis of drivers of smart manufacturing is the original contribution of the authors.

CEO pay sensitivities in innovative firms

Purpose

This study aims to investigate whether compensation committees provide the chief executive officers (CEOs) with incentives to undertake “income-decreasing” but potentially “value-enhancing” innovation expenditures. The authors specifically analyze pay–performance relationships for innovative firms relative to all other firms. This study is critical because innovation is expensive and has uncertain outcomes.

Design/methodology/approach

Using alternative accounting performance measures and market performance measures, the authors estimate an econometric model of CEO compensation in innovative firms that incorporates the interaction of endogenous innovation and firm performance.

Findings

The authors document an incremental positive association between changes in accounting performance measures and CEO compensation changes in innovative firms relative to other firms. This sensitivity of executive pay to firm performance is higher for firms that innovate. These results support the hypothesis that compensation committees provide incentives to carry out risky innovation by tying executive compensation more closely to firm performance. This finding survives a battery of sensitivity tests.

Practical implications

The implications of this study are significant. Capital needs to support risky research and development investments (Tidd and Besant, 2018; Baldwin and Johnson, 1995) form the basis of innovative firms' operations. Considering these expenses, if CEOs, who play a critical role in the scanning, adapting and implementing innovative needs in a firm, are not protected and compensated for making risky choices, the entire investment itself will be threatened. Hence, the findings reiterate and support earlier findings that speak to the importance of compensating CEOs to make high-risk investments that will lead to long-term economic and financial gains for the firm when the innovative behaviors result in competitive market shares and profits.

Originality/value

The original work is related to the investigation of pay–performance sensitivity in the presence of innovation, which has not been fully investigated in prior literature.