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Introduction The purpose of this paper is to discuss the effect on inventory levels of centralisation, i.e., moving from a logistics system formed from a number of field warehouses to one where all demands are met from a single location. In particular, we shall examine the “square root law of locations”, a result which asserts that the total inventory in a system is proportional to the square root of the number of locations at which a product is stocked.

In a recent article Maister discusses the role of centralised inventory in a logistics system and provides a proof of the square root law recognised to be useful for this purpose by several authors (Starr and Miller, Brown, and Heskett et al.). However, the previous authors applied the law to describe the distribution of safety stocks whereas Maister attempts to extend it to the case of cycle stocks as well. The present paper re‐examines the law critically and raises some questions regarding its applicability, especially to the case of cycle stocks. Certain pertinent issues are also discussed at the end.

Today Lionel Penrose is recognised as the co-author of one of the two leading indices of power in voting legislatures – a field of study that game theory in general, and cooperative game theory in particular, has been reclaiming from sociology and political science since the 1950s. The main claim of this paper is that Penrose developed his index so as to tackle questions that go vastly beyond the narrow domain of voting; namely, acute social issues during the Cold War such as the outburst and propagation of panics, the ideological susceptibility of populations, the escalation of military conflict and the successful installation of authoritarian regimes. Furthermore, by revisiting the history of the Penrose power index, the paper re-evaluates some of its key underlying assumptions: assumptions that have been heavily – and unfairly, as the paper argues – criticised over the last decade.

The square root law (SRL) is a popular model for assessing inventory levels when changing the number of warehouses. Previous empirical research, however, has shown that mostly its underlying assumptions do not hold in practice. This sparks the question how inaccurate the SRL’s results are. The paper aims to discuss this issue.

In 26 company cases of reducing the number of warehouses, the estimation error of the SRL is analysed irrespective of its underlying assumptions.

The analysis reveals an average estimation error for total inventory of 27.85 per cent (median=27.84 per cent), but a high variability across the cases. The SRL seems to mostly overestimate inventory savings from centralisation and inventory increases from decentralisation. Managers should only use the SRL if inventory depends on the number of warehouses in their situation, i.e. if they use the economic order or production quantity policy and safety factor approach. Suggestions for coping with the SRL’s estimation error are given.

This paper is based on the 26 cases that could be found in a thorough literature review in the ten most widely spoken languages and that contained or allowed to deduce the necessary information. In order to enable wider generalisations, this sample could be extended.

Most past research has been more theoretical in nature. This research is the first to investigate the SRL’s estimation error using a variety of company cases and how to cope with this error.

The purpose of this paper is to know whether the authors’ productivity pattern of library and information science (LIS) open access journals adheres to Lotka’s inverse square law of scientific productivity. Since the law was introduced, it has been tested in various fields of knowledge, and results have varied. This study has closely followed Lotka’s inverse square law in the field of LIS open access journals to find a factual result and set a baseline for future studies on author productivity of LIS open access journals.

The publication data of selected ten LIS open access journals pertain to authorship, citations were downloaded from the Scopus database and analysed using bibliometric indicators like authorship pattern, collaborative index (CI), degree of collaboration (DC), collaborative coefficient (CC) and citation counts. This study has applied Lotka’s inverse square law to assess authors’ productivity pattern of LIS open access journals and further Kolmogorov-Smirnov (K-S) goodness-of-fit test applied for testing of observed and expected author productivity data.

Inferences were drawn for the set objectives on authorship pattern, collaboration trend and authors’ productivity pattern of LIS open access journals covered in this study. The single authorship pattern is dominant in LIS open access journals covered in this study. The CI, DC and CC are found to be 1.95, 0.47 and 0.29, respectively. The expected values as per Lotka’s law (n = −2) significantly vary from the observed values as per the chi-square test and K-S goodness-of-fit test. Hence, this study does not adhere to Lotka’s inverse square law of scientific productivity.

Researchers may find an idea about the authors’ productivity patterns of LIS open access journals. This study has used the K-S goodness-of-fit test and the chi-square test to validate the authors’ productivity data. The inferences found out from this study will be a baseline for future research on author productivity of LIS open access journals.

This study is significant from the viewpoint of the growing research on open access journals in the field of LIS and to identify the authorship pattern, collaboration trend and author productivity pattern of such journals.

Considers the dynamical effect of lateral emergency transhipments within a supply chain. It tests various different strategies for improving customer service via the MIT Beer Game. Four distinct strategies are considered. “Electronic point of sales (EPOS)”, where marketplace information is forwarded to all players throughout the supply chain; “Excel”, where the stock levels in all echelons are controlled by the factory; “Emergency transhipments”, where an express transportation route bypassing an echelon in the supply chain is permitted; “Eliminate”, where an echelon is removed from the supply chain. The Beer Game strategies are also studied via a simulation exercise. Results show that the Excel strategy is flawed, whereas the EPOS strategy has a strong impact on inventory cost, Emergency transhipments has a strong impact on customer service level and Eliminate results in less stock for an improved customer service level. Combinations of the three viable strategies are also tested. This paper concludes that the three strategies can be integrated to significantly improve supply chain performance.

The purpose of this paper is to examine the likely determinants of the demand for official international reserves (hereafter reserves) for India and China in the long run in a basic buffer stock model. The paper also examines the role of domestic money market disequilibrium in the short-run demand for official reserves for both the countries in a dynamic synthesis model.

The study used quarterly data for the time period 1993:Q1–2015:Q4. The long-run model is being estimated by following the Frenkel–Jovanovic (1981) buffer stock model and includes the determinants such as transaction motive variable (GDP or Imports), opportunity cost variable (domestic interest rate), precautionary motive variable (volatility of reserves) and exchange rate. The study also examined the role of domestic money market disequilibrium in addition to the above variables in the short-run reserve demand model. The money market disequilibrium term is expected to be negative and significant in the short run. The study employed autoregressive distributed lag bound testing approach to co-integration and unrestricted error-correction model (UECM) approach developed by Pesaran et al. (2001) for estimating the long-run and short-run models, respectively.

The co-integration test suggests the existence of long-run relationship between international reserves and its determinants. In the long run, all the variables are statistically significant with expected sign, except domestic interest rate variable for China. It is also found that, the money market disequilibrium term in the short run is negative and significant which validates that an excessive money demand (supply) induces an inflow (outflow) of international reserves for both India and China with a lag of four quarters. The recursive residual tests (CUSUM and CUSUMSQ) confirm the stability of both long-run and short-run reserve demand models.

The findings and policy implications of this study may be useful for the policy makers of the similar emerging economies for designing money and currency policies.

This paper is a comparative study which systematically analyzed the reserve demand behavior of the two emerging economies India and China. The study integrates the domestic money market with the international reserve demand behavior for these two economies.