Model: MistyDragon/bge-small-finetuned
Author: MistyDragon
Pipeline: sentence-similarity
Library: sentence-transformers
Tags: sentence-transformers, safetensors, bert, sentence-similarity, feature-extraction, dense, generated_from_trainer, dataset_size:525, loss:MultipleNegativesRankingLoss, en, arxiv:1908.10084, arxiv:1705.00652, base_model:BAAI/bge-small-en-v1.5, base_model:finetune:BAAI/bge-small-en-v1.5, license:apache-2.0, model-index, text-embeddings-inference, endpoints_compatible, region:us
Base models (finetune): id: BAAI/bge-small-en-v1.5
Card metadata: language: en
license: apache-2.0
tags: sentence-transformers, sentence-similarity, feature-extraction, dense, generated_from_trainer, dataset_size:525, loss:MultipleNegativesRankingLoss
base_model: BAAI/bge-small-en-v1.5
widget: source_sentence: search_document: 60  ◾  Production and Operations Management Systems
can compromise quality. Operations management should try to avoid supporting 
productivity increases gained in this way; the improvement is temporary, at best. 
Other ways of obtaining lower costs such as the use of cheaper components and raw 
materials may lower quality.
The CEO had something else in mind. When requesting increased productiv -
ity, the CEO meant using technology and good P/OM methods to improve the 
process without lowering quality. The CEO’s call for increased productivity is in 
response to competitive strategies.
Decreasing quality to match lower prices is not a way to keep customers. 
Improved productivity, if it is to translate into greater customer satisfaction and 
loyalty, must come from working smarter, not harder. This means improving pro -
ductivity by means other than asking people to work faster, which usually degrades 
quality.
This highlights the strong functional interaction between marketing and P/OM 
(which is emphasized in Chapter 11). The managers of these areas are associates 
working together to manage the effects of price–demand elasticity on production 
costs and on meeting quality standards. Price–demand elasticity is another example 
of a crucial relationship between systems partners (marketing and P/OM) required 
for successful strategic planning.
Elasticity is a rate-of-change measure that expresses the degree to which demand 
grows or shrinks in response to a price change. A product with high elasticity expe-
riences large decreases (increases) in demand as price increases (decreases), whereas 
a product with low elasticity experiences small decreases (increases) in demand with 
the same degree of price increases (decreases). Low elasticity, called inelasticity, 
means that demand levels are relatively insensitive to price changes. Marketing 
managers frequently ask market researchers to study the price elasticity of products 
or services to determine how fast demand falls off as price is increased. Products 
that have no substitutable alternatives (as perceived by customers) usually have low 
elasticity. Product designers who strive for exceptional qualities and production 
managers who demand the highest feasible process qualities are creating barriers to 
substitutability (inelastic products).
Perfect inelasticity—when demand does not change, no matter what the 
price—is an accurate description of the situation when an industrial customer is 
dependent on one supplier for special materials. Most customers try to get out of 
such a constraining situation for obvious reasons.
Elasticity is a complex relationship. The rate of change between price and demand 
is not always smooth and regular. There can be kinks in the line or curve. These 
occur, for example, when an increase in price causes demand to increase, which 
might happen when price becomes high enough to have “snob appeal,” which opens 
a new market. Despite difficulties, it is important to measure elasticity, thereby 
relating price and volume—which are critical factors for production planning.
The elasticity–productivity tie between operations management and marketing 
is attributed to the following:
sentences: search_query: Introduction to Production and Operations Management   ◾  41, search_query: In the context of Production and Operations Management Systems, what is the primary concern when productivity increases are achieved through compromising quality?, search_query: ---------------------, source_sentence: search_document: Supply Chain Management  ◾  361
chain participants. These oscillations are known as bullwhip effect and described in 
the sections on bullwhip effect later in the chapter.
Figures 9.10 and 9.11 show the SOH and orders placed by the retailer and dis-
tributor, respectively. It is evident that large oscillations are costing all participants 
a great deal. This is in spite of the fact that a review of the orders made by both the 
retailer and the distributor leads to the conclusion that the ordering policies fol -
lowed were sensible.
Figure 9.12 compares the end SOH results for the retailer and the distributor. 
The effect had seemed enormous to the retailer. However, when the comparison is 
made with the distributor, the retailer’s swings were gentle. The effect is going to be 
even worse at the producer’s level.
If the increased demand seems to be sustained over a reasonable period of time, 
the producer might invest in more capacity (equipment and people) for what seems 
Week Begin SOHS upply Net SOH End SOHO rder quantity Delivery weekDemand
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*FedEx delivery
*Note that the order for 80 cases made in week 17 is expedited via FedEx at extra cost to
be delivered at the beginning of week 18.
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Figure 9.9 Supply chain simulation of distributors ordering from producers 
(manufacturers).
sentences: search_query: In the context of job evaluation, which of the following methods is NOT typically used by HR professionals?, search_query: Supply Chain Management  ◾  361, search_query: In the context of Function 5, which is related to Production and Operations Management Systems, what are the implications of technological changes on product design and the issuance of Engineering Change Orders (EDCs)?, source_sentence: search_document: 196  ◾  Production and Operations Management Systems
depleted, an order is placed for the EOQ, and further units are taken from Bin 1. Each 
time Bin 2 is emptied, a new order is placed—it is equivalent to reaching the RP. The 
two-bin system is not feasible for many kinds of items. When applicable, much cleri-
cal work is eliminated. This two-bin system is well suited to small items such as nuts, 
bolts, and fasteners. These are items too small and too numerous to make withdrawal 
entries for each transaction. The same reasoning applies to recording withdrawals of 
liquids, for which the two-bin system approach is also ideal. See, for example, the 
application of two-bin system concept in effective management of a nursing ward for 
replenishment of supplies method (http://www.hec.ca/pages/sylvain.landry/en).
5.11 Periodic Review (Fixed Time) Inventory Systems
Periodic inventory systems are based on review of inventory levels at regular fixed 
review periods. These systems were more popular than perpetual inventory systems 
before inventory information was digitized and put online. These were ideally suited for 
manual entries and when actions should be taken periodically rather than randomly.
Computers outmoded periodic manual systems primarily designed to save 
money on the clerical aspects of tracking inventory. However, periodic inventory 
systems continue to be used for other reasons. These include requirements of suppli-
ers concerning the timing for accepting new orders, requirements of shippers about 
timing deliveries, meeting the schedules of customers, and fulfilling the need to 
combine orders to obtain volumes sufficient for shipment discounts.
Some organizations have central warehouses that will only accept orders from 
their regional distributors once in a week. Each region expects deliveries on a dif -
ferent day of the week. Further, some industries prefer the regularity of the periodic 
method, which can be linked to changeover intervals for production processes as 
well as the phases of projects. For example, the stages of buildings must be synchro-
nized with what suppliers deliver.
Periodic inventory systems also play a part in an advanced class of inventory 
models (called Ss policies) that combine the ordering rules of perpetual and peri -
odic order systems to obtain lower total costs. These blended methods can be 
encountered in big inventory systems installations such as the Armed Forces use.
The optimal interval for periodic review, t0, is based on the square root relation-
ship given in the following equation:
 
t S
DH0 = 2 .
The equation for t0 can be derived as follows:
 
t Q
DD
DS
H
S
DH0
0 12 2== ∗= .
sentences: search_query: In the context of the linear breakeven chart, what does the vertical distance between the fixed cost line and the total cost line represent?, search_query: In the context of the preface, how did the rise of complex and large enterprises influence the development of quality management procedures?, search_query: ---------------------, source_sentence: search_document: 82  •  Quality   Management:   Theory   and   Applicatio n
similar disadvantages to an authoritarian style though, with employees 
becoming highly dependent on the leader. If the wrong decisions are made, 
then all employees may become dissatisfied with the leader.
Democratic
In a democratic style, the manager allows the employees to take part in deci-
sion making; therefore, everything is agreed on by the majority. The com-
munication is extensive in both directions (from subordinates to leaders 
and vice versa). This style can be particularly useful when complex decisions 
need to be made that require a range of specialist skills: for example, when 
a new information and communication technologies (ICT) system needs 
to be put in place and the upper management of the business is computer 
illiterate. From the overall business’ point of view, job satisfaction and qual-
ity of work will improve. However, the decision-making process is severely 
slowed down, and the need for a consensus may lead to not taking the “best” 
decision for the business. It can go against a better choice of action.
Laissez-Faire
In a laissez-faire leadership style, the leader’s role is peripheral and staff man-
ages their own areas of the business; the leader therefore evades the duties of 
management, and uncoordinated delegation occurs. The communication in 
this style is horizontal, meaning that it is equal in both directions; however, 
very little communication occurs in comparison with other styles. The style 
brings out the best in highly professional and creative groups of employees; 
however, in many cases it is not deliberate and is simply a result of poor 
management. This leads to a lack of staff focus and sense of direction, which 
in turn leads to much dissatisfaction and a poor company image.
r ewards b ased u PO n Per FO rmance
A psychological reward is a process that reinforces behavior—something 
that, when offered, causes a behavior to increase in intensity. Reward is 
an operational concept for describing the positive value an individual 
ascribes to an object, behavioral act, or internal physical state. Primary 
© 2010 by Taylor and Francis Group, LLC
sentences: search_query: In the context of forecasting demand for the next year, what is the significance of the 'Average SI' (Seasonal Index) in the calculation of forecasted demand for each quarter?, search_query: Workload Assessment (Forecasting)   ◾  115, search_query: In the context of leadership styles, which style is characterized by extensive communication in both directions and is particularly useful when complex decisions need to be made that require a range of specialist skills?, source_sentence: search_document: 386  ◾  Production and Operations Management Systems
10.8  Location Decisions Using the Transportation 
Model
Transportation costs are a primary concern for a new start-up company or division. 
This also applies to an existing company that intends to relocate. Finally, it should 
be common practice to reevaluate the current location of an ongoing business so 
that the impact of changing conditions and new opportunities are not overlooked. 
When shipping costs are critical for the location decision, the transportation model 
(TM) can determine minimum cost or maximum profit solutions that specify opti-
mal shipping patterns between many locations.
Transportation costs include the combined costs of moving raw materials to 
the plant and of transporting finished goods from the plant to one or more ware -
houses. It is easier to explain the TM with the following numerical example than 
with abstract math equations. A doll manufacturer has decided to build a fac -
tory in the center of the United States. More specifically, Missouri and Ohio are 
identified as the potential states. Several sites in the two regions have been identi -
fied. Two cities have been chosen as candidates. These are St Louis, Missouri, and 
Columbus, Ohio. Real-estate costs are about equal in both. The problem is to 
select one of the two cities. The decision will be based on the shipping (transporta -
tion) costs.
10.8.1 Shipping (Transportation or Distribution) Costs
The average cost of shipping (also known as the cost of distribution or cost of trans-
portation) the components that the company uses to the Columbus, Ohio, location 
is $6 per production unit. Shipping costs average only $3 per unit to St Louis, 
Missouri. In TM terminology, shippers (suppliers, in this case) are called sources or 
origins. Those receiving shipments (producers, in this case) are called destinations.
The average cost of shipping from the Columbus, Ohio, location to the 
 market—distributor’s warehouse is $2 per unit. The average cost of shipping from 
St Louis, Missouri, to the market—distributor’s warehouse is $4 per unit. The same 
terminology applies. The shipper is the producer (source or origin) and the receivers 
are the distributors or customers (destinations). The configuration of origins and 
destinations are shown in Figure 10.1.
Total transportation costs to and from the Columbus, Ohio, plant are 
$6 + $2 = $8 per unit; for St Louis, Missouri, they are $3 + $4 = $7. Other things 
being equal, the company should choose St Louis, Missouri. However, the real 
world is not as simple as this.
The problem becomes more complex when there are a number of origins com -
peting for shipments to a number of destinations. We will illustrate the com -
plexity of the problem and its solution using the example of Rukna Auto Parts 
Manufacturing Company.
sentences: search_query: ---------------------, search_query: What is the primary objective of loading in the production scheduling process?, search_query: In the context of the Transportation Model (TM), what are the primary considerations for a company when deciding on a new location for its operations?
pipeline_tag: sentence-similarity
library_name: sentence-transformers
metrics: cosine_accuracy@1, cosine_accuracy@3, cosine_accuracy@5, cosine_accuracy@10, cosine_precision@1, cosine_precision@3, cosine_precision@5, cosine_precision@10, cosine_recall@1, cosine_recall@3, cosine_recall@5, cosine_recall@10, cosine_ndcg@10, cosine_mrr@10, cosine_map@100
model-index: name: BGE Small English v1.5
results: task: type: information-retrieval
name: Information Retrieval
dataset: name: dim 384
type: dim_384
metrics: type: cosine_accuracy@1
value: 0.6893939393939394
name: Cosine Accuracy@1
verified: no, type: cosine_accuracy@3
value: 0.803030303030303
name: Cosine Accuracy@3
verified: no, type: cosine_accuracy@5
value: 0.8484848484848485
name: Cosine Accuracy@5
verified: no, type: cosine_accuracy@10
value: 0.8863636363636364
name: Cosine Accuracy@10
verified: no, type: cosine_precision@1
value: 0.6893939393939394
name: Cosine Precision@1
verified: no, type: cosine_precision@3
value: 0.2676767676767676
name: Cosine Precision@3
verified: no, type: cosine_precision@5
value: 0.16969696969696965
name: Cosine Precision@5
verified: no, type: cosine_precision@10
value: 0.08863636363636362
name: Cosine Precision@10
verified: no, type: cosine_recall@1
value: 0.6893939393939394
name: Cosine Recall@1
verified: no, type: cosine_recall@3
value: 0.803030303030303
name: Cosine Recall@3
verified: no, type: cosine_recall@5
value: 0.8484848484848485
name: Cosine Recall@5
verified: no, type: cosine_recall@10
value: 0.8863636363636364
name: Cosine Recall@10
verified: no, type: cosine_ndcg@10
value: 0.7854028590069935
name: Cosine Ndcg@10
verified: no, type: cosine_mrr@10
value: 0.7530934343434343
name: Cosine Mrr@10
verified: no, type: cosine_map@100
value: 0.7569319824286133
name: Cosine Map@100
verified: no
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Created: 2025-07-22 05:36:33