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Product innovation is central to the success of most companies. The rewards of a successful innovation programme are highly visible in terms of sales, profits and growth. But not so apparent are the strategies that underlie these product innovation efforts. This monograph is about the ingredients of a winning new product strategy — about strategic decisions on markets, technologies, products — that result in a successful innovation programme.

Communications regarding this column should be addressed to Mrs. Cheney, Peabody Library School, Nashville, Tenn. 37203. Mrs. Cheney does not sell the books listed here. They are available through normal trade sources. Mrs. Cheney, being a member of the editorial board of Pierian Press, will not review Pierian Press reference books in this column. Descriptions of Pierian Press reference books will be included elsewhere in this publication.

The digital learning and learning & development (L&D) at workplaces in corporates is having a significant challenge, where only about 1% of the week is spent on L&D by the employees. There are an array of recent L&D reports–by Deloitte, 2019; Skillsoft's, 2019; LinkedIn Workplace Learning Report-2019; UK L&D Report-2019; FICCI-NASSCOM and EY “Future of Jobs” Report-2017–which have clearly been indicating that the digital learning is fast-emerging as one of the realistic option. The employees invest their time and energy for skilling/up-skilling/re-skilling for remaining relevant to the emerging business context under volatility, uncertainty, complexity and ambiguity (VUCA) world and also coronavirus disease 2019 (COVID-19) is being researched.

The L&D interventions have primary objective of enhancing skills, competencies and career growth among employees, and the learning engagement styles/ systems are undergoing dramatic paradigm shifts. There is dire need to understand the impact of sweeping changes with Industry 4.0 and HR 4.0; however, there are only a few industry-centric studies that are available to assess the impact of technology on L&D with digital learning. Hence, there is a need to study the factors influencing various segments of workforce in large corporates, where the learning engagement with digital learning is fast-emerging among corporates.

Given the digital learning / L&D context in corporates, this research paper has attempted to review and analyse the opportunities, challenges and emerging trends with respect to leveraging technology and innovation to enhance L&D to deliver the business goals, under the 70:20:10 framework, with case analysis of ten different corporates (across different industry sectors) viz., Genpact, Nexval, Airbus, Siemens, AstraZeneca Pharma, HPCL, HGS (BPM), HP, Flipkart and IBM. The A-to-Z of Talent Management and Leadership Development (adopted version from India Leadership Academy, Publicis Sapient, 2019) best practices are analysed, summarized and presented to indicate emerging trends in Industry 4.0 era.

This study has been carried out for just ten major corporates/ multinational companies (MNCs) operating in various sectors. The sample size used is relatively less; therefore, the study can be carried out with a larger sample size and deeper data analysis and insights across countries/continents. At present, this can be considered as a base-research for undertaking deep-dive analysis. The sectoral analysis and cross-industry perspectives require consideration in next studies. To address the sector-specific issues, the research can be undertaken for either a particular sector such as manufacturing, automotive, IT/ITeS, telecom, aviation, agri-tech and pharmaceutical, knowledge-based industries, etc. or comparative analysis across few related sectors required.

This research has provided/shall provide a basis to understand the various factors that influence the L&D and digital learning ecosystem in large corporates. It is expected to provide a practical and also strategic perspective towards effective usage of digital learning systems (both in-house and open systems) for enhancing the effectiveness of L&D in the context of VUCA World and HR 4.0 around us. The proposed hypothesis of “The Digital Learning is the “Future of HR”, especially for the L&D in large Corporate Academies (in the context of Industry 4.0)” stands justified.

The clear shift from training culture to “Learning Culture” is possible and feasible with strategically planned digital learning/ L&D interventions, which benefits the corporates, employees, customers and the society at large.

To the best of our knowledge, probably this is one of the first paper in the analysing the industry best L&D/Digital learning practices from an practitioners and academic perspective, as we live in the era of bit-sized and byte sized micro-learning. This study contributes to the academics by providing insights on possible digital learning policies that can be practiced by large corporates, where the “ownership of learning and career growth” is transferred onto the employees. The result of this study complements the evolving digital learning trends, in line with science of self-driven and lifelong learning principle.

This study aims to test the effects of forecast specificity on the asymmetric short‐window share market response to management earnings forecasts (MEF).

The paper examines a large sample of hand‐checked Australian data over the period 1994 to 2001. Using an analyst news benchmark, it estimates a series of regressions to investigate whether the short‐term impact from bad news announcements is greater in magnitude than from good news announcements and whether this differs between routine and non‐routine MEFs. Additionally, it examines whether (after controlling for news content of MEF) there is a differential market impact conditional on specificity: minimum versus maximum versus range versus point.

The results indicate that an asymmetric response is evident for the overall sample and a sub‐set of non‐routine forecasts. Contrary to predictions, the results show that forecast specificity, minimum, maximum, range and point MEFs make no additional contribution to the differences in the market reaction to bad or good news.

The study extends the research investigating the short‐run market impact of MEFs. The main element of innovation derives from the interaction between specificity and news content, as well as distinguishing between routine versus non‐routine cases. Notably, it found little support for the view that more specific forecasts elicit greater market responses. What the results do suggest is that managers appear to choose the form of the forecast to suit the news being delivered. In particular, bad news delivered in a minimum forecast seems to be ignored by the market.

Companies are now looking for more productivity at a faster pace from their research and development organizations. Nowadays, the time it takes to get an innovation to market has become a critical index of global competition. Even companies with world‐renowned R&D capability and significant past successes are striving to enhance their R&D performance and competitive position.

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.

This special “Anbar Abstracts” issue of the Journal of Product & Brand Management is split into ten sections covering abstracts under the following headings: Marketing strategy; Customer service; Pricing; Promotion; Marketing research; Product management; Channel management; Logistics and distribution; New product development; Purchasing.

Scholars have examined the importance of a firm's dividend policy through two competing paradigms: the signalling hypothesis and the free cash‐flow hypothesis. It has been argued that our understanding of dividend policy is hindered by the lack of a model that integrates the two hypotheses. The purpose of this paper is to address this by developing a theoretical dividend model that combines the signalling and free cash‐flow motives. The objective of the analysis is to shed light on the complex relationship between dividend policy, managerial incentives and firm value.

In order to consider the complex nature of dividend policy, a dividend signalling game is developed, in which managers possess more information than investors about the quality of the firm (asymmetric information), and may invest in value‐reducing projects (moral hazard). Hence, the model combines signalling and free cash‐flow motives for dividends. Furthermore, managerial communication and reputation effects are incorporated into the model.

Of particular interest is the case where a firm may need to cut dividends in order to invest in a new value‐creating project, but where the firm will be punished by the market, since investors are behaviourally conditioned to believe that dividend cuts are bad news. This may result in firms refusing to cut dividends, hence passing up good projects. This paper demonstrates that managerial communication to investors about the reasons for the dividend cut, supported by managerial reputation effects, may mitigate this problem. Real world examples are provided to illustrate the complexity of dividend policy.

This work has been inspired by, and develops that of Fuller and Thakor, and Fuller and Blau, which considers the signalling and free cash‐flow motives for dividends. Whereas those authors consider the case where firms only have new negative net present value (NPV) projects available (so that dividend increases provide unambiguously positive signals to the market in both the signalling and free cash‐flow cases), in this paper's model, the signals may be ambiguous, since firms may need to cut dividends to take positive NPV projects. Hence, the model assists in understanding the complexity of dividend policy.

The purpose of this study is to measure the R&D performance of 81 cities in Turkey by using a scientific approach.

A four-step solution approach is developed for this problem. In the first step, a hierarchical structure of 14 indicators (including number of patents, publications, R&D expense, etc.) in three dimensions is constructed. In the second step, explicitly and implicitly spatial indicators such as university location and R&D manpower are mapped by using geographic information system (GIS). In the third step, a hybrid multi-criteria decision making model, namely, DANP that combines decision-making trial and evaluation laboratory (DEMATEL) and analytic hierarchy process (ANP) techniques is applied to assign different level of importance to the indicators. In the last step, Višekriterijumska Optimizacijai kompromisno Rešenje (VIKOR) method is used to rank the performance of 81 cities. Obtained results are visualized using GIS to show the pros and cons of each city in terms of R&D performance.

Results of the paper show that Istanbul, Ankara and Konya are ordered as contenders of best R&D performances and on the contrary, Igdir, Sirnak and Tunceli are ordered as the worst R&D performances among 81 cities.

One limitation of the study can be the considered criteria. However, all the criteria are obtained from literature and experts; thus, the paper covers as much criteria as possible.

The proposed study may allow Ministry of Science, Industry and Technology of Turkey to formulate more effective strategies to improve cities’ R&D performance. In addition, any country can apply the same methodology for measuring the R&D performance of their cities by using their related data. As the worst R&D city performances belong to the eastern part of Turkey, it can be deducted that the socio-cultural structure of the eastern part of the country needs improvement.

To the best of the author’s knowledge, this is the first study which applies a GIS-based MCDM approach for R&D performance measurement. Thus, the value of this paper belongs to both literature and real life.