Corruption and military spending

Anecdotal evidence relates corruption with high levels of military spending. This paper tests empirically whether such a relationship exists. The empirical analysis is based on data from four different sources for up to 120 countries during 1985–1998. The association between military spending and corruption is investigated by using cross-section and panel regression techniques. The results suggest that corruption is associated with higher military spending as a share of both GDP and total government spending, as well as with arms procurement in relation to GDP and total government spending. The results can be interpreted as evidence that defense spending may be used as a component of an indicator of the quality of governance.     

Determinants of Trade Misinvoicing

Trade misinvoicing should be seen as an element of de facto capital account openness. Traditional explanations for trade misinvoicing??high custom duties and weak domestic economies??are less persuasive in a world of high growth emerging markets that have low trade barriers. We construct a 53-country data set over a 26?year span, covering both industrialized and developing countries, to study the phenomena of export and import misinvoicing. Capital account openness, differentials in interest rates, political stability, corruption, indebtedness and the exchange rate regime are identified as factors related to misinvoicing.     

A novel hybrid multi-criteria method for supplier selection among SMEs on the basis of innovation ability

Today, small and large business houses operate collaboratively for the efficiency in the functioning of supply chains. Larger organisations mostly depend on small companies to supply majority of its components and thus they need to be careful while selecting their suppliers. Small organisations performing innovatively and supplying technologically upgraded as well as quality products at a cheaper rate can be a boon for the larger enterprise. This study develops a model for evaluating and selecting small firms as suppliers on the basis of their innovativeness. Best–Worst multi-criteria method is used to rank criteria of innovativeness and also to calculate their weights on the basis of expert opinion. Fuzzy TOPSIS methodology is used to rank the suppliers with respect to these criteria and finally select the best supplier among the available alternatives. A real-world application is illustrated by taking a case of auto component manufacturer and its seven suppliers, 5 main criteria and 23 sub-criteria are taken up for the study.

Abbreviations: AHP: analytical hierarchal process; ANP: analytical network process; DEMATEL: decision-making trail and evaluation laboratory; EMS: environment management system; ELECTRE: ELimination Et Choix Traduisant la REalité (elimination and choice expressing reality); FPIS: fuzzy positive ideal solution; FNIS: fuzzy negative ideal solution; ISM: interpretative structural modelling; PROMTHEE: preference ranking organisation method for enrichment evaluation; SME: small and medium enterprises; TOPSIS: technique for order preference by similarity to ideal solution; QFD: quality function deployment; VIKOR: VlseKriterijuska Optimizacija I Komoromisno Resenje; SP1; SP2; SP3; SP4; SP5; SP6; SP7: Various suppliers used as alternatives     

Hazard analysis and safety considerations in refrigerated ammonia storage tanks

A systematic approach to find out the probability of Ammonia tank failure was adopted and a consequence analysis in case of accidental Ammonia release from refrigerated ammonia storage tanks was made. The study revealed that construction of a concrete bund wall around the tanks is not justified. Instead, it would be adequate to upgrade the safety in the common dyke around the tanks by adopting additional conventional methods.     

The effects of public expenditures on labour productivity in Europe

Empirica - In this paper, we analyse the effects of public expenditures and their structure on productivity growth in industry and services in the European Union (EU) countries (1996–2017)....     

Falling behind and catching up: India's transition from a colonial economy

India fell behind during colonial rule. The absolute and relative decline of Indian GDP per capita with respect to Britain began before colonization and coincided with the rise of the textile trade with Europe. However, the fortunes of the traditional textile industry cannot explain the decline in the eighteenth century and stagnation in the nineteenth century as India integrated into the global economy of the British Empire. Inadequate investment in agriculture and consequent decline in yield per acre stalled economic growth. Modern industries emerged and grew relatively fast. The reversal began after independence. Policies of industrialization and a green revolution in agriculture increased productivity in agriculture and industry. However, India's growth in the closing decades of the twentieth century has been led by services. A concentration of human capital in the service sector has origins in colonial policy. Expenditure on education prioritized higher education, creating an advantage for the service sector. At the same time, the slow expansion of primary education lowered the accumulation of human capital and put India at a disadvantage in comparison with the fast‐growing economies of East Asia.     

Drivers and impact of food inflation in India

Average food inflation in India during 2006–2013 was one of the highest among emerging market economies, and nearly double the inflation witnessed in India during the previous decade. In this paper, we analyse the behaviour and determinants of food inflation over the recent past. Our main findings include that recent surge in food inflation in India is a result of various factors. On the cost side, agricultural wage inflation is found to be a universal driver of food commodities inflation, as well as the aggregate food inflation. The contribution of agricultural wages has increased significantly in the post Mahatma Gandhi National Rural Employment Act era. Fuel inflation has a moderate impact on food inflation and the effects vary across commodities. Our analysis indicates limited role of fuel and international prices, except for in tradeables. Finally, results suggest significant pass-through effects from food to non-food and to the headline inflation.     

Does real U.K. GDP have a unit root? Evidence from a multi-century perspective

ABSTRACT

We employ linear and nonlinear unit-root tests to examine the stationarity of five multi-century historical U.K. series of real output compiled by the Bank of England. Three series span 1270 to 2016 and two series span 1700 to 2016. These datasets represent the longest span of historical real output data available and, thus, provide the environment for which unit-root tests are most powerful. A key feature of our test is its simultaneous allowance for two types of nonlinearity: time-dependent (structural breaks) nonlinearity and state-dependent (asymmetric adjustment) nonlinearity. The key finding of the test, contrary to what other more popular nonlinear unit-root tests suggest, provides strong evidence that the main structure of the five series is a stationary process characterized by an asymmetric nonlinear adjustment and a permanent break affecting both the intercept and the trend. A major policy implication of this finding is fiscal and/or monetary stabilization policies have only temporary effects on the output levels of the United Kingdom.     

Modeling Drivers and Barriers of Artificial Intelligence Adoption: Insights from a Strategic Management Perspective

Artificial intelligence (AI) in business processes and academic research in AI has significantly increased. However, the adoption of AI in organizational strategy is yet to be explored in extant literature. This study proposes two conceptual frameworks showing hierarchical relationships among the various drivers and barriers to AI adoption in organizational strategy. In a two-step approach, the literature study is first done to identify eight drivers of and nine barriers to AI adoption and validated by academic and industry experts. In the second step, MICMAC (matrice d'impacts croises-multiplication appliqúe a un classment or cross-impact matrix multiplication applied to classification) analysis categorizes the drivers and barriers to AI adoption in organizational strategy. Total interpretive structural modeling (TISM) is developed to understand the complex and hierarchical associations among the drivers and barriers. This is the first attempt to model the drivers and barriers using a methodology like TISM, which provides a comprehensive conceptual framework with hierarchical relationships and relative importance of the drivers and barriers to AI adoption. AI solutions' decision-making ability and accuracy are the most influential drivers that influence other driving factors. Lack of an AI adoption strategy, lack of AI talent, and lack of leadership commitment are the most significant barriers that affect other barriers. Recommendations for senior leadership are discussed to focus on the leading drivers and barriers. Also, the limitations and future research scope are addressed.