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In this dynamic era, the market is very competitive and the demand for a product fluctuates every now and then. Under these circumstances, it is quite essential to correctly estimate the market demand to survive the competition. If the estimated demand becomes less, the company loses the business but if the estimated demand is high, the company blocks the working capital till such time the excess production is sold in the market. In view of this, an attempt has been made to explore market demand forecast method selection criteria and apply them in practice to find out which one is most suitable for forecasting the demand for products of the industry in the market. The theoretical part of this study starts with the forecast method classification done by different researchers. The analysis of the different forecast methods reveals that it is rather difficult to determine the advantage of any method in forecast estimation as there always remains the risk of wrong method selection. Each forecast method has its advantages and disadvantages under different situations. Therefore, the analysis and differentiation of the main forecast method selection criteria is expedient. The literature review suggests that the selection of the forecast method should be based on several criteria such as forecast accuracy level, forecast time span, the scope of initial data, and the level of result appropriateness. This study was carried out in Hero MotoCorp Ltd. for the selection of a forecast method most suitable for the company for forecasting the motorcycle demand based on the actual demand experienced by the company for the period April 2016 to March 2017. The comparison of the forecast accuracy assessment indicators that were estimated by using different forecast methods indicates that the lowest motorcycle sales forecast error values were achieved by applying exponential smoothing method where smoothing constant, α = 0.3. [ABSTRACT FROM AUTHOR]

Two dealers of Harley-Davidson Japan who are remarkably different in terms of sales performance were selected and analyzed for a case study. It was found that these dealers were very different in their management of customer-to-customer (C2C) interactions. The high-performing dealer put into practice the following aspects, which were not seen with respect to the low-performing dealer: (i) creating groups of customers in their customer community according to "new owner," "intermediate," and "advanced" groups; and (ii) sponsoring original events for each group. The customer vehicle replacement rate and sales performance rose not only for C2C interactions within groups for activities (i) and (ii) but also for C2C interactions between groups. [ABSTRACT FROM AUTHOR]

Many countries have implemented public bike systems to promote sustainable public transportation. Despite the rapid development of such systems, few studies have investigated how built environment factors affect the use of public bikes at station level using trip data, taking account of the spatial correlation between nearby stations. Built environment factors are strongly associated with travel demand and play an important role in the success of public bike systems. Using trip data from Zhongshan's public bike system, this paper employed a multiple linear regression model to examine the influence of built environment variables on trip demand as well as on the ratio of demand to supply (D/S) at bike stations. It also considered the spatial correlations of PBS usage between nearby stations, using the spatial weighted matrix. These built environment variables mainly refer to station attributes and accessibility, cycling infrastructure, public transport facilities, and land use characteristics. Generally, we found that both trip demand and the ratio of demand to supply at bike stations were positively influenced by population density, length of bike lanes and branch roads, and diverse land-use types near the station, and were negatively influenced by the distance to city center and the number of other nearby stations. However, public transport facilities do not show a significant impact on both demand and D/S at stations, which might be attributed to local modal split. We also found that the PBS usage at stations is positively associated with usage at nearby stations. Model results also suggest that adding a new station (with empty capacity) within a 300 m catchment of a station to share the capacity of the bike station can improve the demand-supply ratio at the station. Referring to both trip demand models and D/S models, regression fits were quite strong with larger R 2 for weekdays than for weekends and holidays, and for morning and evening peak hours than for off-peak hours. These quantitative analyses and findings can be beneficial to urban planners and operators to improve the demand and turnover of public bikes at bike stations, and to expand or build public bike systems in the future. [ABSTRACT FROM AUTHOR]

Age norms tell us at what ages members of society consider it appropriate for us to become potty trained, enter and exit school, start and stop driving a car, get married, have children, retire from work, and even die. So, at what age, if any, should a person start riding a motorcycle? More importantly, at what age should a motorcyclist stop riding? The author conducted ethnographic interviews with approximately 90 motorcyclists over the age of fifty. Findings in this study indicate that just as society has established “social clocks” for other personal and social activities, informal norms operate to establish age boundaries for riding motorcycles. Today's Baby Boomers, in their quest to be “forever young,” however, seem to be stretching and breaking those boundaries, redefining previous limitations on a wide variety of activities, including motorcycling. Although the stigma once associated with motorcycling is waning rapidly, some people still view motorcyclists as deviant. Even those who see riding a motorcycle as a non-deviant mainstream activity, however, tend to view motorcycling as the domain of the young and view motorcyclists over the age of fifty as violating age norms. [ABSTRACT FROM PUBLISHER]

The main aim of this paper is to analyse and evaluate retail trade indicators in Lithuania, reveal the changes during the period 1990-2010, define retail development features, major retail chain parts in the market. The target of the study is retail trade, except the sale of motor vehicles and motorcycles. The social, economic and political processes during the first year of the first decade brought huge changes in retail trade as well as other sectors of Lithuanian economy. Changes in retailing affected social-economical status along with household and disposable income. The demographic variations and consumption patterns reflect the overall national economic trends. Retailing promotes country's economic growth, purchasing power and consumption. The analysis showed that the greatest impact on the retail sector and its territorial changes was made by economic-social factors such as GDP, market potential, average wages, purchasing power, commodity prices, population and its age structure, consumption and savings. Other factors are as follows: geographic location, foreign buyers from the East (Belarus, Russia, etc.), product range and transport infrastructure. While analysing changes in number, size and turnover of retail stores during the period of 1990-2010, maximal and minimal ranges were distinguished. The maximal change range: regional centres that attracted numbers of the inhabitants to purchase goods were cities with higher purchasing power of the residents. Cities particularly standing out in this range were Vilnius, Kaunas, Klaipėda, Šiauliai. Cities with lower capacity were Panevėžys, Utena, Marijampolė, Tauragė. The maximal changes were determined by the increasing number of new retail units in Rietavas, Pagėgiai and Kalvarija municipalities. Many of the rural arias did not satisfy the basic needs of the local residents therefore they had to travel to the centres of district or region. One of the regions with maximal changes, Mažeikiai, had residents with higher purchasing power that was encouraged by Orlen Lietuva, the major oil company in the Baltic region, a slower decrease of population and customers from Latvia. Ignalina region was influenced by tourism, increasing sales in small retail shops by the lakes and resorts. The minimal change of retail business appeared in South-eastern municipalities of Lithuania such as Trakai, Elektrėnai, boarders with Belarus - Švenčionys and Šalčininkai, in the Western part of the country - Šilutė, Kelmė, Neringa municipalities and newly established Kazlų Rūda municipality. These changes were encouraged by an increasing trend to shop in bigger shopping centres that offer wider assortment and discounts, also, decreasing demographic numbers. Neringa municipality was influenced by tourists who chose to dine at local catering establishments, though the retail trade did not include the indicators of this sector. [ABSTRACT FROM AUTHOR]

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