Hiring more labour allows it to increase output. Initially, output may rise faster than the inputs of labour. Each additional worker may not need a computer all to themselves and, up to a point, extra workers can share the same office space. At this stage in its expansion of output in the short run, therefore, the firm is experiencing increasing returns to a factor of production, in this case labour. However, this fortunate situation has its limits.
If the firm continues to expand output by increasing the input of labour with unchanged inputs of capital and land, a point will be reached after which the employment of even more workers brings successively smaller increases in output. For example, there may be so many workers that each one spends some time idle in the queue waiting to use a computer. The input of labour is rising faster than output, and the firm is now experiencing diminishing returns to a factor of production.
Diminishing returns pose a serious constraint on the expansion of a firm in the short run. These relationships between inputs and outputs in the short run influence the firm's costs. Returning to the cable supplier, it is now possible to frame a more precise question: what happens to the costs of producing these services as the firm increases its output of them in the short run?
To analyse this, we need to distinguish total costs TC and the average cost AC of production. A firm's total costs are the expenses incurred in buying the inputs necessary to produce the firm's output.
Average cost is the cost per unit of output. Average cost AC is therefore the total cost of production TC divided by the number of units produced Q :. We can draw a short-run average cost SRAC curve that models the relationship between different levels of output and average cost AC in the short run Figure 5.
Each point on the SRAC curve represents the average cost in the short run measured on the vertical axis of producing a quantity of output measured on the horizontal axis. Output Q is measured per time period, such as a year. The downward-sloping section of the SRAC curve indicates that as output expands from a low level, average costs in the short run fall.
Eventually, however, the SRAC curve begins to slope upwards, showing that at output levels above Q 1 average costs rise as output increases. The shape of the SRAC curve arises from the technical constraints on short-run output expansion just described. We assume that the price of inputs is constant. As output expands the fixed cost of the fixed factors of production, such as the cable system itself, is being spread over an expanded number of customers.
Increasing returns to a factor of production means that output rises faster than the variable input, so the cost of the variable factor per unit of output falls too. So initially the average cost of production AC falls as output rises. Eventually, however, diminishing returns to the variable factor of production sets in. Output starts to rise more slowly than the variable input so the additional cost required to produce additional units of output starts to rise. Eventually total cost fixed plus variable costs will start to rise faster than output: that is, average costs will start to rise.
On Figure 5 this happens as output rises above Q 1. To sum up, in the short run the firm's ability to reduce costs as output rises is constrained by diminishing returns. In the long run, opportunities to invest in factors such as plant and machinery mean that the quantity of all factors of production can be varied. How does that affect the firm's costs? Making the decision to study can be a big step, which is why you'll want a trusted University.
Take a look at all Open University courses. If you are new to University-level study, we offer two introductory routes to our qualifications. You could either choose to start with an Access module , or a module which allows you to count your previous learning towards an Open University qualification. Read our guide on Where to take your learning next for more information. Not ready for formal University study? Then browse over free courses on OpenLearn and sign up to our newsletter to hear about new free courses as they are released.
In this case, technology 1 is the low-cost production technology. This example shows that as an input becomes more expensive in this case, the labor input , firms will attempt to conserve on using that input and will instead shift to other inputs that are relatively less expensive.
This pattern helps to explain why the demand curve for labor or any input slopes down; that is, as labor becomes relatively more expensive, profit-seeking firms will seek to substitute the use of other inputs. However, that same employer is likely to use production technologies with more workers and less machinery when producing in a lower-wage country like Mexico, China, or South Africa.
One final point: an improvement in production technology is a new method of production, or a new process, that produces more output with the same amount of inputs, or it produces the same output using less inputs. Thus, an improvement in production technology leads to a reduction in production cost. Privacy Policy. Skip to main content. Module 7: Production and Costs. Search for:.
Try It. Glossary production technologies: alternative methods of combining inputs to produce output. Manufacturing SMEs can also acquire the scientific and innovative knowledge necessary to develop radically new products from organizations [ 49 ]. If a firm has high organization capacity to integrate outsourced knowledge and technology into internal knowledge, the effects that the outsourced knowledge and technology have on product innovation will be increased [ 50 ].
With the advent of the information revolution, skills and knowledge have become the only sources of a sustainable long-term competitive advantage. The rising importance of intellectual property can be seen in the earnings gained from the licensing of technology. In the past, firms were willing to share their technology, as it did not appear to be a source of their success and could not be sold for much in any case.
However, knowledge-based industries are important in their own right, and firms can buy or license external knowledge through IP, including the licensing of patents and copyrights or trademarks at a lower cost.
Therefore, firms are no longer willing to share their knowledge and technology without being compensated for it. Technology licensing allows firms to obtain relatively fast and inexpensive access to new and more advanced technologies. The manufacturing SMEs in our study can also internally develop and create new knowledge using inward IP licensing. With inward IP licensing, manufacturing SMEs can accumulate and strengthen their technological capability from the search and use of external technology [ 52 ].
This will result in the achievement of greater product innovation [ 51 ]. Thus, valuable knowledge from IP licensing influences product innovation [ 51 ]. All of the arguments thus far lead us to argue that firms which carry out technology-exploration activities are likely have an upper hand in achieving product innovation. The survey used here was implemented in and was based on a manual a set of integral guidelines for the collection of innovation data; see OECD, [ 17 ].
The Oslo manual distinguishes innovation as either based on a product, process, organization or marketing innovation [ 17 , 53 ].
Oslo manual is technology innovation guideline for small business [ 17 ]. This guideline contains seven characteristics: objectives and scope of manual, needs for the measurement of innovation, basic definitions, TPP innovation activities, institutional classification, measuring aspects of the innovation process, measuring the expenditure on innovation, and survey procedures [ 17 ].
We selected product innovation, as it is related to the development of new products and services. Respondents had to be employed in their current jobs for at least 5 years and involved in open innovation. Our sample targeted manufacturing SMEs with no more than employees, and data was collected from to The sample contains manufacturing SMEs that tried to achieve product innovation through technology-exploration activities during the 3 years prior to the survey.
Our final sample contains firms that remained in the survey for the 3 years. Launch new product completely differs from existing product, 2. Launch highly improved product compared to existing product, and 3. None of these are applicable. We defined these criterions as dummy variables.
Product innovation performance measurement has always been a difficult task for researchers and has been handled in different ways depending on the purpose of the research [ 54 , 55 ]. We use two dichotomous variables to measure the degree of newness of product innovation. High indicates innovations with a higher degree of novelty.
This is defined as radical innovation in the literature. It involves developing and introducing new products that can fulfill key customer needs better than currently existing products. It takes a value of 1 when a firm declares new product functions resulting from innovation; otherwise its value is 0. LOW indicates an incremental product innovation. This is defined as incremental innovation in the literature.
It involves minor improvements or simple adjustments of a current product. It takes a value of 1 for innovation with a lower degree of novelty e.
We eliminate external participation in this model as it is too difficult to acquire related data due to the fact that manufacturing SMEs generally do not invest in external participation activities such as corporate venture capital CVC investments or joint ventures.
The variable CI can have an integral value between 0 and 10 depending on the degree of customer participation and on how much the customer contributed to the process of product innovation. Customers contribute to product innovation by providing information related to their needs, participating in the development phase of technology, providing core technology solutions, and commercializing the innovative prototype or product.
These were given integral values of 1, 2, 3, and 4, respectively. If a firm undertakes customer involvement, it is possible to sum up the values according to this method and set the maximum CI variable to Scales of investment, sales, and profits of firms vary with the characteristics of the industry field.
Furthermore, the higher the investment ratio is, the more likely product innovation is affected. The EXNT variable, an integral value between 0 and 12, depends on the diversity of the collaborative networks of a firm. The degree of network diversity is related to creating the knowledge that affects product innovation.
We use the number of external network categories in which manufacturing SMEs collaborate to analyze the effect of the external network on product innovation. Earlier research suggests that the knowledge and technology acquired from inward IP licensing contributes to developing the new knowledge needed for product innovation. This new knowledge may influence the product innovation of manufacturing SMEs. Size is measured by average sales Sizes during the 3-year sample period [ 57 , 58 ].
Globalization is measured as the ratio of total exports to total sales Glob to show that exports and internationalization have positive significant effects on innovation [ 59 ]. Globalization is a variable that determines if the competition in the global market influences the demand for product innovation. We developed a model of the relationship between product innovation and open innovation practice using a bivariate probit model.
As both dependent variables, HIGH and LOW, are dichotomous 0,1 , estimation models such as the logit or probit model would be appropriate [ 60 ]. However, as the error terms of the two models are likely to be correlated, an extension of the probit model known as bivariate probit [ 61 ] is usually a more appropriate estimator.
The bivariate probit model has the following specifications:. We can then test if the correlation between the equations is statistically significant and decide whether or not the bivariate estimator is the most appropriate model. If this correlation of the equations is not significant, a separate univariate probit estimation of the equations is preferable, as the bivariate probit model is less efficient. The bivariate probit model was estimated using the Stata 10 routine based on the simulated maximum likelihood method.
The model that includes all variables is the following model:. We used the bivariate probit model to test the impact of technology exploration with data from to This shows that the bivariate model is the correct specification. The Wald test also indicated the high joint significance of the variables in both models. External networking and inward IP licensing have no significant impact on the probability of achieving product innovation, both with a low and a high degree of novelty.
Size has a negative and significant impact on the likelihood of achieving product innovation, both with a low and a high degree of novelty. Globalization has no significant impact on the likelihood of achieving product innovation, both with a low and a high degree of novelty as well.
Manufacturing firms are subject to rapid technological changes and a constant need to innovate more quickly and in more novel ways compared to their competitors. Product innovation performance is measured as radical and incremental innovation to gauge the degree of the novelty of product innovation.
Our results show that technology exploration is crucial regarding whether a low or a higher degree of novelty is achieved in product innovation in manufacturing SMEs. Customer involvement has a positive impact on both incremental and radical innovation. Other practices have no impact on either incremental or radical innovation.
Our findings might offer several practical implications for the manufacturing SMEs that try to achieve incremental or radical innovations. For the incremental innovation, capturing the needs of influential customers can help them realize new solution ideas [ 62 ], quickly identify market trends, and enhance new technology applications. In this process, Organizational filters and routines are deeply involved in satisfying customer needs [ 23 ].
They develop organizational routines to carry out the repetitive tasks of manufacturing and distributing large volumes of their current products efficiently. They can maximize the utility of current technology for their customers and strive toward efficiently developing incremental innovations through these routines [ 64 ].
Our findings imply that customer involvement is also important for radical innovation in manufacturing SMEs. Radical innovation is the development of new products or services that yield much greater benefits to customer compared to those that use older products or services [ 23 ]. Customers contribute to radical innovation by actively participate in the process of the development of a new product as an inventor or co-producer of innovation [ 29 ].
They contribute substantially to the development of highly innovative and commercially attractive products [ 29 ]. Their customers are also manufacturing firms who are sensitive to market changes; thus, they want to be supplied with a component or product that can lead their market. They actively engage in the product development process by providing innovative ideas or opinions to suppliers and playing the role of the lead user in their industry, thus contributing to radical innovation.
Research organizations research institutes and universities are important centers and valuable sources for creating and disseminating the scientific knowledge necessary to develop radically new products [ 65 ]. This study makes important theoretical contribution. In this research, we firstly classified innovation into levels of degree.
By doing so, we could deduct necessary factors for each levels of innovation and empirically verified their relationships. For the innovation performance, antecedent researches mostly focused on measuring numbers of innovation, especially number of patent. This study proposed new way of measure innovation to differentiates from existing studies and provide possibility to verify innovation performance using probit or logit model.
Our findings provide a better understanding of how much technology-exploration practices affect product performance in manufacturing SMEs. This research demonstrates an analysis related to product innovation of manufacturing SMEs; however, it did not classify sample manufacturing SMEs into groups in depth.
Although the data are reliable, our analysis may ignore the characteristics of each classified group according to the customer and product. Manufacturing SMEs need to know various types of customer-related information, such as their customer needs, preferences, purchasing procedures, and the procedures related to the distribution and sales access to the customers in various sample groups. A conclusion about the complex relationships between each classified category group and product innovation requires a longitudinal study, which should be undertaken in the future.
Teece DJ Profiting from technological innovation: implications for integration, collaboration, licensing and public policy. Res Policy 15 6 — Article Google Scholar. Chesbrough HW Open innovation: the new imperative for creating and profiting from technology.
Harvard Business Press, Boston. Google Scholar. Oxford University Press, London. Gassmann O Opening up the innovation process: towards an agenda.
Nieto MJ, Santamaria L The importance of diverse collaborative networks for the novelty of product innovation. Technovation 27 6—7 — Shin S, Lee M The effect of innovation activities on innovation performance according to the size of SMEs in the field of electronics and communication industry. Soc Korea Ind Systs Eng 37 1 — Hwang G-I A study on the present state and development plan of Korean small and medium sized firms. J manag Res Namseoul Univer — IMD The world competitiveness yearbook.
Freel MS Barriers to product innovation in small manufacturing firms. Int Small Bus J 18 2 —
0コメント