As the desires of market get various, so its demand fluctuates frequently. The only companies that flexibly meets fluctuating demands can survive in the fierce market competition. In this study, we deal with the development of jig system for manual welding processes that can cause flexible actions and uniform quality in the manufacturing shock absorber base assembly of automobile. For this we review the processes of design and development through analysis of the technology and the customer that are patents analysis, customer desires analysis, functional analysis and so on. Moreover, we review the relevant indicators for improvement of productivity that are production capacity, cycle time and error rates etc. as the technology is developed.
Cross-buying refers to the customer action of buying additional products and/or services
from the same provider (Valentin 2004). With the belief that cross-buying enables firms
to increase profit from existing customers, firms have steadily placed greater emphasis on
cross-selling strategies for profitability.
To date, numerous studies show that cross-buying behavior of customers has a positive
effect on firm profitability. Business reality, however, offers a different perspective;
namely, that high levels of cross-buying may not always be linked to firm profitability.
For example, Best Buy (an electronics retailer in the United States) has identified
approximately 20% of its customers as unprofitable in spite of them purchasing multiple
items (McWilliams 2004). Shah, Kumar, Qu, and Chen (2012) found that customers who
persistently exhibit certain types of behavior (e.g., excessive service requests, high levels
of returning products, lower levels of revenue growth, promotion maximizers) are
unprofitable even though they purchased more than one product category.The aforementioned research implies that cross-buying can exert a negative impact on
profitability, thereby calling for further examination of cross-buying behavior. It is
conceivable that a repeated purchase propensity (contrasted with a cross-buying
propensity) concentrated on a single brand is more profitable.
Therefore, our primary objective in this paper is to identify a more beneficial type of
customer among those who tend to patronize a limited number of brands versus those
who tend to patronize a variety of brands, using a one-dimensional model (brand
dispersion index). In addition, the second goal of this research is to investigate the
boundary conditions where cross-buying will not lead to an increase in sales (unprofitable
cross-buying conditions). As two moderating factors that weaken a customer’s crossbuying
propensity and a firm’s sales (frequency and transaction size of firms), we
consider (1) promotion dependency and (2) spending limiter condition.
We use transaction data that include partners in various industries such as gasoline
stations, convenience stores, banks, restaurants, and online shopping malls, covering
forty-seven categories. Because multiple partners in many categories are available, this allows us to study whether a customer’s cross-buying level in the current period (t)
affects the customer’s purchase frequency and transaction size in the subsequent period
(t+1). The observation period for the data set extends over three years.
Findings from this study indicate that a high level of cross-buying at period t has a
positive impact on increasing customer frequencies and transaction sizes in the
subsequent (t+1) period. This means that cross-buying has the potential to increase the
firm’s profitability. Customers who show a high level of cross-buying propensity tend to
exhibit higher levels of loyalty than customers who concentrated on limited brands. Firms
should find ways to induce customers with low cross-buying propensity to increase crossbuying.
Regarding moderating effects, promotion dependency and spending growth (decline vs.
stagnation), spending growth has a considerable moderating effect on the relationship
between cross-buying propensity and a customer’s transaction size. Specifically, the
effect of cross-buying on transaction size weakens when spending is shrinking. This
result makes an important contribution to cross-buying research. If customers showing a
high level of cross-buying do not increase their spending level, they may be merely
switching to other brands in the program under a fixed budget. So while the rate of crossbuying
seems to increase, profit might not increase. The findings from this study imply
that it is crucial to target and motivate customers who tend to use various brands and
contribute to sales to do more cross-buying instead of suggesting cross-buying to random
customers.
The promotion dependency, however, turns out to not have significant moderating effects
on the relationship between the customer’s propensity to cross-buying and the customer’s
purchase frequency and transaction size.
For marketing purposes, it is important to consider which customers are more profitable
among those who tend to do cross-buying among multi-brands versus those who tend to
purchase repeatedly in a limited number of brands. This research provides a solution with
a one-dimensional index, the brand dispersion index. Whether cross-buying is shown to
be a positive or negative impact on sales, the results are meaningful in implementing
customer relationship management. Regardless of the direction in the level of crossbuying,
both directions provide a solution to allocate marketing resources. For instance, if
the propensity for cross-buying increases sales, the firm should implement marketing
strategies to encourage people to use a variety of brands by adding new brands. If repeat
purchases increase sales, the company should concentrate on certain brands that
customers use most frequently.
In addition, by finding the conditions that do not increase sales (e.g., spending limiter
condition), it makes marketing practitioners think that cross-buying does not always bring
positive results. Overall, the findings from this study are that it is crucial to motivate and
target customers who tend to use various brands and contribute to sales to do crossbuying
activity, instead of promoting cross-buying to random customers.
Conceptual Framework
Figure 1 provides an overview of our framework for the relationship between brand dispersion and visiting frequency and transaction size of customers. Specifically, we hypothesize how customer frequencies and transaction sizes in time t+1 will be influenced by customer brand dispersion levels (the extent that customer transactions occur across a broad range of brands) in time t. In addition, we examine the moderating influence of two customer specific variables: (1) degree of promotion dependency and (2) spending limits.
SERPINB3 (also known Squamous cell carcinoma antigen 1, SCCA1) is involved in apoptosis, immune response, cell migration and invasiveness of cells. It has been investigated in various types of squamous cell carcinoma. Therefore we investigated the functional role of SERPINB3 gene in human epithelial ovarian cancer (EOC) using laying hens, the most relevant animal model. In 136 laying hens, EOC was found in 10 (7.4%). We compared the expression and localization of SERPINB3 using RT-PCR, quantitative RT-PCR, in situ hybridization and immunohistochemistry, and SERPINB3 activation was detected in chicken and human ovarian cancer cell lines using immunofluorescence microscopy. Thereafter, we examined the prognostic value of SERPINB3 expression in patients with EOC by multivariate linear logistic regression and Cox’ proportional hazard analyses. In present study, SERPINB3 mRNA was induced in cancerous ovaries (p< 0.01), and it was only expressed in the glandular epithelium(GE) of cancerous ovaries of laying hens. SERPINB3 protein was localized predominantly to the nucleus of glandular epithelium in cancerous ovaries of laying hens, and it was abundant in the nucleus of both chicken and human ovarian cancer cell lines. In 109 human patients with EOC, 15 (13.8%), 66 (60.6%) and 28 (25.7%) of those patients showed weak, moderate and strong expression of SERPINB3 protein, respectively. Strong expression of SERPINB3 protein was a prognostic factor for platinum resistance (adjusted OR, 5.94; 95% Confidence Limits, 1.21-29.15). Therefore SERPINB3 may play an important role in ovarian carcinogenesis and be a novel biomarker for predicting platinum resistance and a poor prognosis for survival in patients with EOC. This research was funded by the World Class University (WCU) program (R31-10056), Basic Science Research Program (2010- 0013078) through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science, and Technology and by the Next-Generation BioGreen 21 Program (No.PJ008142), Rural Development Administration, Republic of Korea.